Pub Date : 2016-11-01DOI: 10.1109/ICORAS.2016.7872600
C. S. Ee, K. Sim, V. Teh, F. F. Ting
Computed tomography (CT) is the initial imaging modality for stroke diagnoses. However, efficient approach to estimate window setting for CT brain images is not yet founded. Window setting consists of 2 components: window center (WC) and window width (WW). In this paper, a novelty estimation method namely estimation of window width using mean of greyscale level to standard deviation ratio (EWWMGSR) is developed to determine the WW for CT brain images, with WC is fixed as 40 HU. The results show the robustness of EWWMGSR method in determining the estimated WW value, compared with prior existing approaches. Most of them are determined manually and within a very small range. EWWMGSR estimates better window width value for radiologists in CT brain image diagnoses.
{"title":"Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio","authors":"C. S. Ee, K. Sim, V. Teh, F. F. Ting","doi":"10.1109/ICORAS.2016.7872600","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872600","url":null,"abstract":"Computed tomography (CT) is the initial imaging modality for stroke diagnoses. However, efficient approach to estimate window setting for CT brain images is not yet founded. Window setting consists of 2 components: window center (WC) and window width (WW). In this paper, a novelty estimation method namely estimation of window width using mean of greyscale level to standard deviation ratio (EWWMGSR) is developed to determine the WW for CT brain images, with WC is fixed as 40 HU. The results show the robustness of EWWMGSR method in determining the estimated WW value, compared with prior existing approaches. Most of them are determined manually and within a very small range. EWWMGSR estimates better window width value for radiologists in CT brain image diagnoses.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122174789","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 : 2016-11-01DOI: 10.1109/ICORAS.2016.7872631
I. Iszaidy, A. Alias, R. Ngadiran, R. B. Ahmad, M. Jais, D. Shuhaizar
As traffic continues to grow up, the issue regarding the road accident also growing quickly. The accident occurred due to the high speed of vehicles on the road. This paper proposed a vehicle speed detection and travel time estimation system using Raspberry Pi to estimate the speed of passing vehicles through this system. The system is designed to detect the moving vehicles and calculate its velocity. The system used OpenCV as an image processing software to detect and track the moving vehicles. Several types of capturing size of the video are used in this system to check and measure the performance of the embedded board.
{"title":"Video size comparison for embedded vehicle speed detection & travel time estimation system by using Raspberry Pi","authors":"I. Iszaidy, A. Alias, R. Ngadiran, R. B. Ahmad, M. Jais, D. Shuhaizar","doi":"10.1109/ICORAS.2016.7872631","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872631","url":null,"abstract":"As traffic continues to grow up, the issue regarding the road accident also growing quickly. The accident occurred due to the high speed of vehicles on the road. This paper proposed a vehicle speed detection and travel time estimation system using Raspberry Pi to estimate the speed of passing vehicles through this system. The system is designed to detect the moving vehicles and calculate its velocity. The system used OpenCV as an image processing software to detect and track the moving vehicles. Several types of capturing size of the video are used in this system to check and measure the performance of the embedded board.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123273552","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 : 2016-11-01DOI: 10.1109/ICORAS.2016.7872625
F. F. Ting, Kok-Swee Sim, Y. Lee
A 3D reconstruction method using surface interpolation with the interfacing of Hermite surface (SIHE) is proposed to construct a 3D model from a series of breast images. This method aim to visualize the diagnosed result from the 2D gray scale Digital Imaging and Communications in Medicine (DICOM) images. It provides an attractive 3D model for doctors to have a better explanation regarding the diagnosed result to the patients. A series of 2D breast DICOM images are obtained by using magnetic resonance imaging (MRI). Then, the images are sorted by using the image sorting system. After the breast images are sorted, the 3D reconstruction method is utilized to construct the 3D model. By comparing the proposed method with existing methods, the proposed method has utilized the breasts lesion detection to classify breast lesions during the 3D reconstruction process. Thus, the tabulated results show that SIHE outperforms other existing methods in similar field.
{"title":"Three-dimensional model reconstruction using surface interpolation with the interfacing of Hermite surface for breast cancer MRI imaging system","authors":"F. F. Ting, Kok-Swee Sim, Y. Lee","doi":"10.1109/ICORAS.2016.7872625","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872625","url":null,"abstract":"A 3D reconstruction method using surface interpolation with the interfacing of Hermite surface (SIHE) is proposed to construct a 3D model from a series of breast images. This method aim to visualize the diagnosed result from the 2D gray scale Digital Imaging and Communications in Medicine (DICOM) images. It provides an attractive 3D model for doctors to have a better explanation regarding the diagnosed result to the patients. A series of 2D breast DICOM images are obtained by using magnetic resonance imaging (MRI). Then, the images are sorted by using the image sorting system. After the breast images are sorted, the 3D reconstruction method is utilized to construct the 3D model. By comparing the proposed method with existing methods, the proposed method has utilized the breasts lesion detection to classify breast lesions during the 3D reconstruction process. Thus, the tabulated results show that SIHE outperforms other existing methods in similar field.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127777902","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 : 2016-11-01DOI: 10.1109/ICORAS.2016.7872633
T. K. Kho, K. Sim, F. F. Ting
This paper presents a colour-based and contour based segmentation methods to aid doctors in Gastrointestinal (GI) Endoscopy examination process. These methods are proposed to enhance existing GI Endoscopy image processing applications. Based on the previous existing GI image processing applications, these algorithms are developed to assist doctor in diagnosis process while identifying the type of disease in the intestine. For the image processing part, as compared to previous existing methods, colour-based detection is justified to be the easiest and accurate way for detecting the reflux, lesion and bleeding as they differ in colour.
{"title":"Gastrointestinal endoscopy colour-based image processing technique for bleeding, lesion and reflux","authors":"T. K. Kho, K. Sim, F. F. Ting","doi":"10.1109/ICORAS.2016.7872633","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872633","url":null,"abstract":"This paper presents a colour-based and contour based segmentation methods to aid doctors in Gastrointestinal (GI) Endoscopy examination process. These methods are proposed to enhance existing GI Endoscopy image processing applications. Based on the previous existing GI image processing applications, these algorithms are developed to assist doctor in diagnosis process while identifying the type of disease in the intestine. For the image processing part, as compared to previous existing methods, colour-based detection is justified to be the easiest and accurate way for detecting the reflux, lesion and bleeding as they differ in colour.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129845653","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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