Titlebook: Medical Imaging in Clinical Applications; Algorithmic and Comp Nilanjan Dey,Vikrant Bhateja,Aboul Ella Hassanien Book 2016 Springer Interna

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Book 2016parts, Part-I: Clinical Applications of Medical Imaging, Part-II: Classification and clustering, Part-III: Computer Aided Diagnosis (CAD) Tools and Case Studies and Part-IV: Bio-inspiring based Computer Aided diagnosis techniques... .

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Development of EOG and EMG-Based Multimodal Assistive Systems aid) and communications support systems. The user details were registered and the system operability was monitored in the same GUI. Due to multitasking and ease of use of the proposed device, the quality of life of the incapacitated individuals can be improved with greater independence.

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Book 2016ter aided diagnosis approaches as well as different techniques for solving the pectoral muscle extraction problem in the preprocessing part of the CAD systems for detecting breast cancer in its early stage using digital mammograms. The aim of this book is to stimulate further research in medical ima

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Abdominal Imaging in Clinical Applications: Computer Aided Diagnosis Approaches. Thus, the identification of distinct algorithms to model the organs and abnormalities it is vital for understanding anatomy and disease. Moreover, a survey on CAD based abdominal image enhancement, segmentation, classification and fusion is included. Finally, challenging topics are addressed to explore new fields for development.

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Abdominal Imaging in Clinical Applications: Computer Aided Diagnosis Approachesf CAD systems would provide anatomical knowledge coupled with image processing procedures to improve diagnosis/healthcare. For accurate diagnosis and treatment, researchers are interested with clinical image analysis. Since, the abdominal organs are characterized by complexity and high inconsistency

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An Overview of Pectoral Muscle Extraction Algorithms Applied to Digital Mammogramstedious job of continuously observing the mammograms in fatigue. Hence, the early detection of cancer with more accuracy is highly expected to reduce the death rate. Computer Aided Detection (CADe) can help radiologists in providing a second opinion increasing the overall accuracy of detection. Pect

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Magnetic Resonance Brain Imaging Segmentation Based on Cascaded Fractional-Order Darwinian Particle segmentation. Therefore, medical image segmentation technique is required to develop an efficient, fast diagnosis system. In this paper, we proposed a segmentation framework that is based on Fractional-order Darwinian Particle Swarm Optimization (FODPSO) and Mean Shift (MS) techniques. In pre-proces