Pub Date : 2019-07-24DOI: 10.5772/INTECHOPEN.83581
Tassadaq Hussain, Amna Haider, Muhammad Shafique, A. Taleb-Ahmed
Medical imaging is classified into different modalities such as ultrasound, X-ray, com- puted tomography (CT), positron emission tomography (PET), magnetic resonance imaging (MRI), single-photon emission tomography (SPECT), nuclear medicine (NM), mammography, and fluoroscopy. Medical imaging includes various imaging diagnostic and treatment techniques and methods to model the human body, and therefore, performs an essential role to improve the health care of the community. Medical imaging, scans (such as X-Ray, CT, etc.) are essential in a variety of medical health-care environments. With the enhanced health-care management and increase in availability of medical imaging equipment, the number of global imaging-based systems is growing. Effective, safe, and high-quality imaging is essential for the medical decision-making. In this chapter, we proposed a medical imaging-based high-performance hardware architecture and soft- ware programming toolkit called high-performance medical imaging system (HPMIS). The HPMIS can perform medical image registration, storage, and processing in hardware with the support of C/C++ function calls. The system is easy to program and gives high performance to different medical imaging applications.
{"title":"A High-Performance System Architecture for Medical Imaging","authors":"Tassadaq Hussain, Amna Haider, Muhammad Shafique, A. Taleb-Ahmed","doi":"10.5772/INTECHOPEN.83581","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.83581","url":null,"abstract":"Medical imaging is classified into different modalities such as ultrasound, X-ray, com- puted tomography (CT), positron emission tomography (PET), magnetic resonance imaging (MRI), single-photon emission tomography (SPECT), nuclear medicine (NM), mammography, and fluoroscopy. Medical imaging includes various imaging diagnostic and treatment techniques and methods to model the human body, and therefore, performs an essential role to improve the health care of the community. Medical imaging, scans (such as X-Ray, CT, etc.) are essential in a variety of medical health-care environments. With the enhanced health-care management and increase in availability of medical imaging equipment, the number of global imaging-based systems is growing. Effective, safe, and high-quality imaging is essential for the medical decision-making. In this chapter, we proposed a medical imaging-based high-performance hardware architecture and soft- ware programming toolkit called high-performance medical imaging system (HPMIS). The HPMIS can perform medical image registration, storage, and processing in hardware with the support of C/C++ function calls. The system is easy to program and gives high performance to different medical imaging applications.","PeriodicalId":339802,"journal":{"name":"Medical Imaging and Image-Guided Interventions","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133027065","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 : 2019-07-24DOI: 10.5772/INTECHOPEN.76608
A. Sulieman, M. Alkhorayef
The discovery of X-rays at the end of the nineteenth century is one of the most important discoveries that changed the human being life in all fields and applications. Since that date, X-ray systems are developed rapidly, and still new applications are emerging in medical, agricultural, and industrial fields. This chapter provides sufficient historical background for X-ray production and image acquisition techniques. It covers also fluoroscopic equipment and radiation dosimetry and protection techniques in detail. Image-guided intervention is here to stay. Thus, suitable radiation protection measures are required to minimize the risk to patients and staff to its minimal level without affecting the outcome of the procedures.
{"title":"Medical Imaging and Image-Guided Interventions","authors":"A. Sulieman, M. Alkhorayef","doi":"10.5772/INTECHOPEN.76608","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.76608","url":null,"abstract":"The discovery of X-rays at the end of the nineteenth century is one of the most important discoveries that changed the human being life in all fields and applications. Since that date, X-ray systems are developed rapidly, and still new applications are emerging in medical, agricultural, and industrial fields. This chapter provides sufficient historical background for X-ray production and image acquisition techniques. It covers also fluoroscopic equipment and radiation dosimetry and protection techniques in detail. Image-guided intervention is here to stay. Thus, suitable radiation protection measures are required to minimize the risk to patients and staff to its minimal level without affecting the outcome of the procedures.","PeriodicalId":339802,"journal":{"name":"Medical Imaging and Image-Guided Interventions","volume":"1 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117003506","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 : 2018-11-05DOI: 10.5772/INTECHOPEN.81119
Mahmudur Rahman, N. Alpaslan
This paper presents an integrated system for the breast cancer detection from mammo- grams based on automated mass detection, classification, and retrieval with a goal to support decision-making by retrieving and displaying the relevant past cases as well as predicting the images as benign or malignant. It is hypothesized that the proposed diagnostic aid would refresh the radiologist’s mental memory to guide them to a precise diagnosis with concrete visualizations instead of only suggesting a second diagnosis like many other CAD systems. Towards achieving this goal, a Graph-Based Visual Saliency (GBVS) method is used for automatic mass detection, invariant features are extracted based on using Non-Subsampled Contourlet transform (NSCT) and eigenvalues of the Hessian matrix in a histogram of oriented gradients (HOG), and finally classification and retrieval are performed based on using Support Vector Machines (SVM) and Extreme Learning Machines (ELM), and a linear combination-based similarity fusion approach. The image retrieval and classification performances are evaluated and compared in the benchmark Digital Database for Screening Mammography (DDSM) of 2604 cases by using both the precision-recall and classification accuracies. Experimental results dem - onstrate the effectiveness of the proposed system and show the viability of a real-time clinical application.
{"title":"A Decision Support System (DSS) for Breast Cancer Detection Based on Invariant Feature Extraction, Classification, and Retrieval of Masses of Mammographic Images","authors":"Mahmudur Rahman, N. Alpaslan","doi":"10.5772/INTECHOPEN.81119","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.81119","url":null,"abstract":"This paper presents an integrated system for the breast cancer detection from mammo- grams based on automated mass detection, classification, and retrieval with a goal to support decision-making by retrieving and displaying the relevant past cases as well as predicting the images as benign or malignant. It is hypothesized that the proposed diagnostic aid would refresh the radiologist’s mental memory to guide them to a precise diagnosis with concrete visualizations instead of only suggesting a second diagnosis like many other CAD systems. Towards achieving this goal, a Graph-Based Visual Saliency (GBVS) method is used for automatic mass detection, invariant features are extracted based on using Non-Subsampled Contourlet transform (NSCT) and eigenvalues of the Hessian matrix in a histogram of oriented gradients (HOG), and finally classification and retrieval are performed based on using Support Vector Machines (SVM) and Extreme Learning Machines (ELM), and a linear combination-based similarity fusion approach. The image retrieval and classification performances are evaluated and compared in the benchmark Digital Database for Screening Mammography (DDSM) of 2604 cases by using both the precision-recall and classification accuracies. Experimental results dem - onstrate the effectiveness of the proposed system and show the viability of a real-time clinical application.","PeriodicalId":339802,"journal":{"name":"Medical Imaging and Image-Guided Interventions","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129872373","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 : 2018-11-05DOI: 10.5772/INTECHOPEN.81667
T. Gomi
Digital tomosynthesis (DT) is a notable modality in medical imaging because it shows the spread of the target area with lower radiation dose relative to computed tomography. In this section, we describe the technique in two parts: (1) image quality (contrast) and (2) DT image reconstruction algorithms, including state-of-the-art total variation minimization reconstruction algorithms with single-energy X-ray conventional polychromatic imaging and novel dual-energy (DE) virtual monochromatic imaging. The novel DE virtual monochromatic image-processing algorithm provides adequate overall performance (especially, reduction of beam-hardening, reduction of noise). The DE virtual monochromatic image-processing algorithm appears to be a promising new option for imaging in DT because it provides three-dimensional visualizations of high-contrast images that are far superior to those of images processed by using conventional single-energy polychromatic image- processing algorithms.
{"title":"State-Of-The-Art X-Ray Digital Tomosynthesis Imaging","authors":"T. Gomi","doi":"10.5772/INTECHOPEN.81667","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.81667","url":null,"abstract":"Digital tomosynthesis (DT) is a notable modality in medical imaging because it shows the spread of the target area with lower radiation dose relative to computed tomography. In this section, we describe the technique in two parts: (1) image quality (contrast) and (2) DT image reconstruction algorithms, including state-of-the-art total variation minimization reconstruction algorithms with single-energy X-ray conventional polychromatic imaging and novel dual-energy (DE) virtual monochromatic imaging. The novel DE virtual monochromatic image-processing algorithm provides adequate overall performance (especially, reduction of beam-hardening, reduction of noise). The DE virtual monochromatic image-processing algorithm appears to be a promising new option for imaging in DT because it provides three-dimensional visualizations of high-contrast images that are far superior to those of images processed by using conventional single-energy polychromatic image- processing algorithms.","PeriodicalId":339802,"journal":{"name":"Medical Imaging and Image-Guided Interventions","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116211207","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 : 2018-03-19DOI: 10.5772/INTECHOPEN.75163
E. Mendoza, N. Abi-Jaoudeh
Minimally invasive liver directed therapies have established their role in the treatment of hepatic neoplasms. The Barcelona Clinic staging systems is the most widely used staging system and combines staging and management. While surgical resection or liver trans- plantation are commonly performed for very early stage cancers, patient ’ s typically pre-sent with advanced disease. For those with single or small lesions, percutaneous tumor ablation may be curative. Transarterial chemoembolization or radioembolization are palliative treatments reserved for those with unresectable tumors or as bridge to transplant. In this chapter, we discuss the role of liver directed therapies throughout various stages of liver cancer, the management of these procedures, and its impact on patient care.
{"title":"Liver Directed Therapies","authors":"E. Mendoza, N. Abi-Jaoudeh","doi":"10.5772/INTECHOPEN.75163","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.75163","url":null,"abstract":"Minimally invasive liver directed therapies have established their role in the treatment of hepatic neoplasms. The Barcelona Clinic staging systems is the most widely used staging system and combines staging and management. While surgical resection or liver trans- plantation are commonly performed for very early stage cancers, patient ’ s typically pre-sent with advanced disease. For those with single or small lesions, percutaneous tumor ablation may be curative. Transarterial chemoembolization or radioembolization are palliative treatments reserved for those with unresectable tumors or as bridge to transplant. In this chapter, we discuss the role of liver directed therapies throughout various stages of liver cancer, the management of these procedures, and its impact on patient care.","PeriodicalId":339802,"journal":{"name":"Medical Imaging and Image-Guided Interventions","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116999030","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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