Pub Date : 2021-01-01DOI: 10.4236/jbise.2021.1412034
Christos Barbagiannis, Alexios A Polydorou, M. Zervakis, A. Polydorou, Eleftheria Sergaki
The proposed deep learning algorithm will be integrated as a binary classifier under the umbrella of a multi-class classification tool to facilitate the automated detection of non-healthy deformities, anatomical landmarks, pathological findings, other anomalies and normal cases, by examining medical endoscopic images of GI tract. Each binary classifier is trained to detect one specific non-healthy condition. The algorithm analyzed in the present work expands the ability of detection of this tool by classifying GI tract image snapshots into two classes, depicting haemorrhage and non-haemorrhage state. The proposed algorithm
{"title":"Detection of Angioectasias and Haemorrhages Incorporated into a Multi-Class Classification Tool for the GI Tract Anomalies by Using Binary CNNs","authors":"Christos Barbagiannis, Alexios A Polydorou, M. Zervakis, A. Polydorou, Eleftheria Sergaki","doi":"10.4236/jbise.2021.1412034","DOIUrl":"https://doi.org/10.4236/jbise.2021.1412034","url":null,"abstract":"The proposed deep learning algorithm will be integrated as a binary classifier under the umbrella of a multi-class classification tool to facilitate the automated detection of non-healthy deformities, anatomical landmarks, pathological findings, other anomalies and normal cases, by examining medical endoscopic images of GI tract. Each binary classifier is trained to detect one specific non-healthy condition. The algorithm analyzed in the present work expands the ability of detection of this tool by classifying GI tract image snapshots into two classes, depicting haemorrhage and non-haemorrhage state. The proposed algorithm","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70883049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/jbise.2021.1412035
R. LeMoyne, Timothy Mastroianni
The quantification of gait is uniquely facilitated through the conformal wearable and wireless inertial sensor system, which consists of a profile comparable to a bandage. These attributes advance the ability to quantify hemiplegic gait in consideration of the hemiplegic affected leg and unaffected leg. The recorded inertial sensor data, which is inclusive of the gyroscope signal, can be readily transmitted by wireless means to a secure Cloud. Incorporating Python to automate the post-processing of the gyroscope signal data can enable the development of a feature set suitable for a machine learning platform, such as the Waikato Environment for Knowledge Analysis (WEKA). An assortment of machine learning algorithms, such as the multilayer perceptron neural network, J48 decision tree, random forest, K-nearest neighbors, logistic regression, and naïve Bayes, were evaluated in terms of classification accuracy and time to develop the machine learning model. The K-nearest neighbors achieved optimal performance based on classification accuracy achieved for differentiating between the hemiplegic affected leg and unaffected leg for gait and the time to establish the machine learning model. The achievements of this research endeavor demonstrate the utility of amalgamating the conformal wearable and wireless inertial sensor with machine learning algorithms for distinguishing the hemiplegic affected leg and unaffected leg during gait. for characterizing the sagittal plane of the thighs during gait. The Y-direction gyroscope signal was the basis for composing the feature set for machine learning classification. The sampling rate of the BioStamp nPoint was set to 250 Hz.
通过保形可穿戴和无线惯性传感器系统，步态的量化是唯一方便的，该系统由一个类似绷带的轮廓组成。考虑到偏瘫的影响腿和未受影响的腿，这些属性提高了量化偏瘫步态的能力。记录的惯性传感器数据，包括陀螺仪信号，可以很容易地通过无线方式传输到一个安全的云。将Python集成到陀螺仪信号数据的自动后处理中，可以开发适合机器学习平台的功能集，例如Waikato Environment for Knowledge Analysis (WEKA)。各种机器学习算法，如多层感知器神经网络、J48决策树、随机森林、k近邻、逻辑回归和naïve贝叶斯，在分类精度和开发机器学习模型的时间方面进行了评估。基于区分偏瘫患腿和未患腿步态的分类精度和建立机器学习模型的时间，k近邻算法获得了最优性能。本研究的成果表明，将保形可穿戴和无线惯性传感器与机器学习算法相结合，可以在步态中区分偏瘫的影响腿和未影响腿。用于描述步态时大腿矢状面。y方向陀螺仪信号是构成机器学习分类特征集的基础。设置BioStamp nPoint的采样率为250hz。
{"title":"Implementation of Machine Learning Classification Regarding Hemiplegic Gait Using an Assortment of Machine Learning Algorithms with Quantification from Conformal Wearable and Wireless Inertial Sensor System","authors":"R. LeMoyne, Timothy Mastroianni","doi":"10.4236/jbise.2021.1412035","DOIUrl":"https://doi.org/10.4236/jbise.2021.1412035","url":null,"abstract":"The quantification of gait is uniquely facilitated through the conformal wearable and wireless inertial sensor system, which consists of a profile comparable to a bandage. These attributes advance the ability to quantify hemiplegic gait in consideration of the hemiplegic affected leg and unaffected leg. The recorded inertial sensor data, which is inclusive of the gyroscope signal, can be readily transmitted by wireless means to a secure Cloud. Incorporating Python to automate the post-processing of the gyroscope signal data can enable the development of a feature set suitable for a machine learning platform, such as the Waikato Environment for Knowledge Analysis (WEKA). An assortment of machine learning algorithms, such as the multilayer perceptron neural network, J48 decision tree, random forest, K-nearest neighbors, logistic regression, and naïve Bayes, were evaluated in terms of classification accuracy and time to develop the machine learning model. The K-nearest neighbors achieved optimal performance based on classification accuracy achieved for differentiating between the hemiplegic affected leg and unaffected leg for gait and the time to establish the machine learning model. The achievements of this research endeavor demonstrate the utility of amalgamating the conformal wearable and wireless inertial sensor with machine learning algorithms for distinguishing the hemiplegic affected leg and unaffected leg during gait. for characterizing the sagittal plane of the thighs during gait. The Y-direction gyroscope signal was the basis for composing the feature set for machine learning classification. The sampling rate of the BioStamp nPoint was set to 250 Hz.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70883111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/jbise.2021.149028
B. Ferry, J. Abraham
{"title":"Mechanical Design of Long-Term Body-Adhered Medical Devices to Maximize On-Body Survival","authors":"B. Ferry, J. Abraham","doi":"10.4236/jbise.2021.149028","DOIUrl":"https://doi.org/10.4236/jbise.2021.149028","url":null,"abstract":"","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70883578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/jbise.2021.1412032
Szu-Hung Chen, Yu-Ru Wang, Yih Ho, Shuhua Lin, Hsuan-Liang Liu
The aberrant overexpression of cyclin-dependent kinase 9 (CDK9) in cancer cells results in the loss of proliferative control, making it an attractive therapeutic target for various cancers. However, the highly structural similarity between CDK9 and CDK2 makes the development of novel selective CDK9 inhibitors a challenging task and thus limits their clinical applications. Here, an effective two-stage virtual screening strategy was developed to identify novel CDK9 inhibitors with better inhibitory activity and higher selectivity. The first screening stage aims to select potential compounds with better inhibitory activity than Roniciclib, one of the most effective CDK9 inhibitors, through reliable structure-based phar-macophoric virtual screening and accurate molecular docking analyses. The second stage employs a very detailed visual inspection process, in solvation energy and/or reducing polar solvation energy can significantly improve the binding affinity of these CDK9 inhibitors. Their clinical potentials to serve as anticancer drug candidates can be further evaluated through a series of in vitro/in vivo bioassays in the future. To the best of our knowledge, this is the first attempt to identify novel CDK9 inhibitors with both better inhibitory activity and higher selectivity through an effective two-stage virtual screening strategy.
{"title":"Identification of Novel CDK9 Inhibitors with Better Inhibitory Activity and Higher Selectivity for Cancer Treatment by an Effective Two-Stage Virtual Screening Strategy","authors":"Szu-Hung Chen, Yu-Ru Wang, Yih Ho, Shuhua Lin, Hsuan-Liang Liu","doi":"10.4236/jbise.2021.1412032","DOIUrl":"https://doi.org/10.4236/jbise.2021.1412032","url":null,"abstract":"The aberrant overexpression of cyclin-dependent kinase 9 (CDK9) in cancer cells results in the loss of proliferative control, making it an attractive therapeutic target for various cancers. However, the highly structural similarity between CDK9 and CDK2 makes the development of novel selective CDK9 inhibitors a challenging task and thus limits their clinical applications. Here, an effective two-stage virtual screening strategy was developed to identify novel CDK9 inhibitors with better inhibitory activity and higher selectivity. The first screening stage aims to select potential compounds with better inhibitory activity than Roniciclib, one of the most effective CDK9 inhibitors, through reliable structure-based phar-macophoric virtual screening and accurate molecular docking analyses. The second stage employs a very detailed visual inspection process, in solvation energy and/or reducing polar solvation energy can significantly improve the binding affinity of these CDK9 inhibitors. Their clinical potentials to serve as anticancer drug candidates can be further evaluated through a series of in vitro/in vivo bioassays in the future. To the best of our knowledge, this is the first attempt to identify novel CDK9 inhibitors with both better inhibitory activity and higher selectivity through an effective two-stage virtual screening strategy.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70883388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/JBISE.2021.142008
M. Fowora, F. U. Onyeaghasiri, Abdullateef O. Olanlege, I. O. Edu-Muyideen, Olumide Adebesin
Dermatophytes were earlier reported to respond well to anti-fungal agents; however, an upsurge in resistance with the high cost of these agents increased the use of medicinal plants for treatment. This study investigated the sensitivity pattern of dermatophytes to oral anti-fungal drugs and aqueous leaf extract of the plant, Acacia nilotica. The extract was tested against seven strains of dermatophytes Arthroderma otae, Trichophyton interdigitale, Trichophyton mentagrophyte, Microsporum ferrugineum, Arthroderma vespertilii, Arthroderma quadrifidum, and Arthroderma multifidum, previously isolated from diabetic patients. The minimum inhibitory and fungicidal concentrations of the plant extracts and the standard antifungal agents were evaluated using modifications of the broth macro dilution method of the National Committee for Clinical Laboratory Standards M38-A2 protocol. There was a significant difference in the Minimum Inhibitory concentrations (MIC) of the dermatophytes to the three antifungal drugs tested (p Acacia nilotica had an inhibitory effect on all the dermatophytes tested, and showed anti-fungal activity in a dose-dependent relationship between 0.625 - 1.25 mg/ml. Though the inhibitions of the dermatophytes were significantly higher with the standard anti-fungal drugs as compared to the plant extract (p Arthroderma quadrifidum, which was resistant to all the anti-fungal drugs, had the highest inhibition with A. nilotica. Some circulating dermatophyte strains in Nigeria are griseofulvin and/or itraconazole resistant which may influence the spread of infection and A. nilotica aqueous leaf extract showed a strong anti-dermatophytic activity.
{"title":"In Vitro Susceptibility of Dermatophytes to Anti-Fungal Drugs and Aqueous Acacia nilotica Leaf Extract in Lagos, Nigeria","authors":"M. Fowora, F. U. Onyeaghasiri, Abdullateef O. Olanlege, I. O. Edu-Muyideen, Olumide Adebesin","doi":"10.4236/JBISE.2021.142008","DOIUrl":"https://doi.org/10.4236/JBISE.2021.142008","url":null,"abstract":"Dermatophytes were earlier reported to respond well to anti-fungal agents; however, an upsurge in resistance with the high cost of these agents increased the use of medicinal plants for treatment. This study investigated the sensitivity pattern of dermatophytes to oral anti-fungal drugs and aqueous leaf extract of the plant, Acacia nilotica. The extract was tested against seven strains of dermatophytes Arthroderma otae, Trichophyton interdigitale, Trichophyton mentagrophyte, Microsporum ferrugineum, Arthroderma vespertilii, Arthroderma quadrifidum, and Arthroderma multifidum, previously isolated from diabetic patients. The minimum inhibitory and fungicidal concentrations of the plant extracts and the standard antifungal agents were evaluated using modifications of the broth macro dilution method of the National Committee for Clinical Laboratory Standards M38-A2 protocol. There was a significant difference in the Minimum Inhibitory concentrations (MIC) of the dermatophytes to the three antifungal drugs tested (p Acacia nilotica had an inhibitory effect on all the dermatophytes tested, and showed anti-fungal activity in a dose-dependent relationship between 0.625 - 1.25 mg/ml. Though the inhibitions of the dermatophytes were significantly higher with the standard anti-fungal drugs as compared to the plant extract (p Arthroderma quadrifidum, which was resistant to all the anti-fungal drugs, had the highest inhibition with A. nilotica. Some circulating dermatophyte strains in Nigeria are griseofulvin and/or itraconazole resistant which may influence the spread of infection and A. nilotica aqueous leaf extract showed a strong anti-dermatophytic activity.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"14 1","pages":"74-82"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70883856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/jbise.2021.1411031
Grace Tam-Nurseman, Philip Achimugu, Oluwatolani Achimugu, H. Anabi, Sseggujja Husssein
Expert systems are being utilized increasingly in medical fields for the purposes of assisting diagnosis and treatment planning. Existing systems used few symptoms for dental diagnosis. In Dentistry, few symptoms are not enough for diagnosis. In this research, a conditional probability model (Bayes rule) was developed with increased number of symptoms associated with a disease for diagnosis. A test set of recurrent cases was then used to test the diagnostic capacity of the system. The generated diagnosis matched that of the human experts. The system was also tested for its capacity to handle uncommon dental diseases and the system portrayed useful potential.
{"title":"Expert System for the Diagnosis and Prognosis of Common Dental Diseases Using Bayes Network","authors":"Grace Tam-Nurseman, Philip Achimugu, Oluwatolani Achimugu, H. Anabi, Sseggujja Husssein","doi":"10.4236/jbise.2021.1411031","DOIUrl":"https://doi.org/10.4236/jbise.2021.1411031","url":null,"abstract":"Expert systems are being utilized increasingly in medical fields for the purposes of assisting diagnosis and treatment planning. Existing systems used few symptoms for dental diagnosis. In Dentistry, few symptoms are not enough for diagnosis. In this research, a conditional probability model (Bayes rule) was developed with increased number of symptoms associated with a disease for diagnosis. A test set of recurrent cases was then used to test the diagnostic capacity of the system. The generated diagnosis matched that of the human experts. The system was also tested for its capacity to handle uncommon dental diseases and the system portrayed useful potential.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70883278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/jbise.2021.1412039
Jorge Santiago Amaya, Cristhian Alejandro Romero González, Kevin Alexis Aguilar Bailon
The electrical stimulation systems dedicated to generating unconventional waveforms have been shown to have a positive effect in the treatment of channelopathies, for example, in open-angle glaucoma. However, these signals can be distorted due to different external circumstances, which could lead to counterproductive effects in treatments such as increased intraocular pressure IOP or other effects that are unknown due to poor electrical signaling. In the present work, a web control system capable of communicating with transcorneal electrical stimulation equipment is proposed for the remote control of treatments applied to patients suffering from various ocular channelopathies. As the first phase of this system, it will only focus on treating patients with open-angle glaucoma since this disease is characterized by an increase in IOP and can be immediately measured by an ophthalmologist.
{"title":"Web Control System for Transcorneal Electric Stimulation Devices","authors":"Jorge Santiago Amaya, Cristhian Alejandro Romero González, Kevin Alexis Aguilar Bailon","doi":"10.4236/jbise.2021.1412039","DOIUrl":"https://doi.org/10.4236/jbise.2021.1412039","url":null,"abstract":"The electrical stimulation systems dedicated to generating unconventional waveforms have been shown to have a positive effect in the treatment of channelopathies, for example, in open-angle glaucoma. However, these signals can be distorted due to different external circumstances, which could lead to counterproductive effects in treatments such as increased intraocular pressure IOP or other effects that are unknown due to poor electrical signaling. In the present work, a web control system capable of communicating with transcorneal electrical stimulation equipment is proposed for the remote control of treatments applied to patients suffering from various ocular channelopathies. As the first phase of this system, it will only focus on treating patients with open-angle glaucoma since this disease is characterized by an increase in IOP and can be immediately measured by an ophthalmologist.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70883677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/jbise.2021.1410029
R. Sakai, Tatsuki Kitazato, K. Uchiyama, Kazuhiro Yoshida, Takeaki Yamamoto, N. Takahira, M. Ujihira
Background: The 1st peak frequency of the hammering sound in total hip arthroplasty may serve as an evaluation index to prevent intraoperative fracture. Fixation of the stem and femur cannot be acquired unless the 1st peak frequency of hammering the stem into the femur stabilizes, and fixation can be judged as acquired when the 1st peak frequency becomes constant. To investigate whether the environmental sound in the operating room can be differentiated from the hammering sound of total hip arthroplasty, the 1st peak frequency of the hammering sound when impacting the stem into the femur with a hammer was identified. Method: The hammering sound of impacting the stem into a biomechanical test material through an impactor was analyzed using a fast Fourier transform analyzer. Environmental sound in the operating room was simulated and the 1st peak frequency of the sound on collision between the operator’s voice and the surgical instrument was measured. The 1st peak frequency of hammering sound was compared between patients indicated for total hip arthroplasty and healthy individuals to investigate whether there is a difference due to bone quality. Results: The natural frequency of the impactor was 3.41 ± 0.05 kHz, and the 1st peak frequency of the femur, stem, and impactor was 2.43 ± 1.45 kHz. The 1st peak frequency of hammering sound on simulated femur in patients indicated for total hip arthroplasty was 2.98 ± 0.73 kHz and that in healthy individuals was 2.15 ± 0.32 kHz. This sug-gested that the hammering sound in total hip arthroplasty-indicated patients overlaps with the frequency of the collision sound of surgical instruments. Conclusion: To develop a sys-Open
{"title":"Investigation of Hammering Sound Frequency to Prevent Intraoperative Fracture during Total Hip Arthroplasty","authors":"R. Sakai, Tatsuki Kitazato, K. Uchiyama, Kazuhiro Yoshida, Takeaki Yamamoto, N. Takahira, M. Ujihira","doi":"10.4236/jbise.2021.1410029","DOIUrl":"https://doi.org/10.4236/jbise.2021.1410029","url":null,"abstract":"Background: The 1st peak frequency of the hammering sound in total hip arthroplasty may serve as an evaluation index to prevent intraoperative fracture. Fixation of the stem and femur cannot be acquired unless the 1st peak frequency of hammering the stem into the femur stabilizes, and fixation can be judged as acquired when the 1st peak frequency becomes constant. To investigate whether the environmental sound in the operating room can be differentiated from the hammering sound of total hip arthroplasty, the 1st peak frequency of the hammering sound when impacting the stem into the femur with a hammer was identified. Method: The hammering sound of impacting the stem into a biomechanical test material through an impactor was analyzed using a fast Fourier transform analyzer. Environmental sound in the operating room was simulated and the 1st peak frequency of the sound on collision between the operator’s voice and the surgical instrument was measured. The 1st peak frequency of hammering sound was compared between patients indicated for total hip arthroplasty and healthy individuals to investigate whether there is a difference due to bone quality. Results: The natural frequency of the impactor was 3.41 ± 0.05 kHz, and the 1st peak frequency of the femur, stem, and impactor was 2.43 ± 1.45 kHz. The 1st peak frequency of hammering sound on simulated femur in patients indicated for total hip arthroplasty was 2.98 ± 0.73 kHz and that in healthy individuals was 2.15 ± 0.32 kHz. This sug-gested that the hammering sound in total hip arthroplasty-indicated patients overlaps with the frequency of the collision sound of surgical instruments. Conclusion: To develop a sys-Open","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70882736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/jbise.2021.146025
Tudor Florin Ursuleanu, Andreea Roxana Luca, L. Gheorghe, Roxana Grigorovici, Stefan Iancu, Maria Hlusneac, C. Preda, A. Grigorovici
Rationale and Objectives: Accurately establishing the diagnosis and staging of cervical and thyroid cancers is essential in medical practice in determining tumor extension and dissemination and involves the most accurate and effective therapeutic approach. For accurate diagnosis and staging of cervical and thyroid cancers, we aim to create a diagnostic method, optimized by the algorithms of artificial intelligence and validated by achieving accurate and favorable results by conducting a clinical trial, during which we will use the diagnostic method optimized by artificial intelligence (AI) algorithms, to avoid errors, to increase the understanding on interpretation computer tomography (CT) scan, magnetic resonance imaging (MRI) of the doctor and improve therapeutic planning. Materials and Methods: The optimization of the computer assisted diagnosis (CAD) method will consist in the development and formation of artificial intelligence models, using algorithms and tools used in segmental volumetric constructions to generate 3D images from MRI/CT. We propose a comparative study of current developments in “DICOM” image processing by volume rendering technique, the use of the transfer function for opacity and color, shades of gray from “DICOM” images projected in a three-dimensional space. We also use artificial intelligence (AI), through the technique of Generative Adversarial Networks (GAN), which has proven to be effective in representing complex data distributions, as we do in this study. Validation of the diagnostic method, optimized by algorithm of artificial intelligence will consist of achieving accurate results on diagnosis and staging of cervical and thyroid cancers by conducting a randomized, controlled clinical trial, for a period of 17 months. Results: We will validate the CAD method through a clinical study and, secondly, we use various network topologies specified above, which have produced promising results in the tasks of image model recognition and by using this mixture. By using this method in medical practice, we aim to avoid errors, provide precision in diagnosing, staging and establishing the therapeutic plan in cancers of the cervix and thyroid using AI. Conclusion: The use of the CAD method can increase the quality of life by avoiding intra and postoperative complications in surgery, intraoperative orientation and the precise determination of radiation doses and irradiation zone in radiotherapy.
{"title":"The Use of Artificial Intelligence on Segmental Volumes, Constructed from MRI and CT Images, in the Diagnosis and Staging of Cervical Cancers and Thyroid Cancers: A Study Protocol for a Randomized Controlled Trial","authors":"Tudor Florin Ursuleanu, Andreea Roxana Luca, L. Gheorghe, Roxana Grigorovici, Stefan Iancu, Maria Hlusneac, C. Preda, A. Grigorovici","doi":"10.4236/jbise.2021.146025","DOIUrl":"https://doi.org/10.4236/jbise.2021.146025","url":null,"abstract":"Rationale and Objectives: Accurately establishing the diagnosis and staging of cervical and thyroid cancers is essential in medical practice in determining tumor extension and dissemination and involves the most accurate and effective therapeutic approach. For accurate diagnosis and staging of cervical and thyroid cancers, we aim to create a diagnostic method, optimized by the algorithms of artificial intelligence and validated by achieving accurate and favorable results by conducting a clinical trial, during which we will use the diagnostic method optimized by artificial intelligence (AI) algorithms, to avoid errors, to increase the understanding on interpretation computer tomography (CT) scan, magnetic resonance imaging (MRI) of the doctor and improve therapeutic planning. Materials and Methods: The optimization of the computer assisted diagnosis (CAD) method will consist in the development and formation of artificial intelligence models, using algorithms and tools used in segmental volumetric constructions to generate 3D images from MRI/CT. We propose a comparative study of current developments in “DICOM” image processing by volume rendering technique, the use of the transfer function for opacity and color, shades of gray from “DICOM” images projected in a three-dimensional space. We also use artificial intelligence (AI), through the technique of Generative Adversarial Networks (GAN), which has proven to be effective in representing complex data distributions, as we do in this study. Validation of the diagnostic method, optimized by algorithm of artificial intelligence will consist of achieving accurate results on diagnosis and staging of cervical and thyroid cancers by conducting a randomized, controlled clinical trial, for a period of 17 months. Results: We will validate the CAD method through a clinical study and, secondly, we use various network topologies specified above, which have produced promising results in the tasks of image model recognition and by using this mixture. By using this method in medical practice, we aim to avoid errors, provide precision in diagnosing, staging and establishing the therapeutic plan in cancers of the cervix and thyroid using AI. Conclusion: The use of the CAD method can increase the quality of life by avoiding intra and postoperative complications in surgery, intraoperative orientation and the precise determination of radiation doses and irradiation zone in radiotherapy.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70883526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/JBISE.2021.142005
Jie Cheng, Lucy T. Zhang
In this study, a finite element simulation of in-stent restenosis (ISR) is conducted to simulate the deployment and expansion of a stent in an occluded artery with a contact model and a mechanics-based growth model. A tissue growth model based on the multiplicative decomposition of deformation is applied to investigate the growth of the plaque and artery wall upon the stent’s implantation. Due to the high stresses at the contact points between the stent struts and the tissue, further tissue injury or restenosis is observed. The simulation results show that after the stent deployment, the von Mises stress is significantly larger in the plaque compared to the artery wall, especially in the region that is in contact with the stent. However, the growth of the plaque and artery tends to even out the stress concentration over time. The tissue growth is found to be more significant near the inner wall than the outer layer. A 0.77 mm restenosis is predicted, which agrees with published clinical observations. The features of the artery growth are carefully analyzed, and the underlying mechanism is discussed. This study is the first attempt to apply finite element analysis to artery restenosis, which establishes a framework for predicting ISR’s occurrence and severity. The results also provide insights into understanding the underlying mechanism of in-stent restenosis.
{"title":"Finite Element Simulation of In-Stent Restenosis with Tissue Growth Model","authors":"Jie Cheng, Lucy T. Zhang","doi":"10.4236/JBISE.2021.142005","DOIUrl":"https://doi.org/10.4236/JBISE.2021.142005","url":null,"abstract":"In this study, a finite element simulation of in-stent restenosis (ISR) is conducted to simulate the deployment and expansion of a stent in an occluded artery with a contact model and a mechanics-based growth model. A tissue growth model based on the multiplicative decomposition of deformation is applied to investigate the growth of the plaque and artery wall upon the stent’s implantation. Due to the high stresses at the contact points between the stent struts and the tissue, further tissue injury or restenosis is observed. The simulation results show that after the stent deployment, the von Mises stress is significantly larger in the plaque compared to the artery wall, especially in the region that is in contact with the stent. However, the growth of the plaque and artery tends to even out the stress concentration over time. The tissue growth is found to be more significant near the inner wall than the outer layer. A 0.77 mm restenosis is predicted, which agrees with published clinical observations. The features of the artery growth are carefully analyzed, and the underlying mechanism is discussed. This study is the first attempt to apply finite element analysis to artery restenosis, which establishes a framework for predicting ISR’s occurrence and severity. The results also provide insights into understanding the underlying mechanism of in-stent restenosis.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"14 1","pages":"33-47"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70883790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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