Computational intelligence in biomedical imaging
著者
書誌事項
Computational intelligence in biomedical imaging
Springer, c2014
- : hbk
大学図書館所蔵 全3件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references
内容説明・目次
内容説明
Computational Intelligence in Biomedical Imaging is a comprehensive overview of the state-of-the-art computational intelligence research and technologies in biomedical images with emphasis on biomedical decision making. Biomedical imaging offers useful information on patients' medical conditions and clues to causes of their symptoms and diseases. Biomedical images, however, provide a large number of images which physicians must interpret. Therefore, computer aids are demanded and become indispensable in physicians' decision making. This book discusses major technical advancements and research findings in the field of computational intelligence in biomedical imaging, for example, computational intelligence in computer-aided diagnosis for breast cancer, prostate cancer, and brain disease, in lung function analysis, and in radiation therapy. The book examines technologies and studies that have reached the practical level, and those technologies that are becoming available in clinical practices in hospitals rapidly such as computational intelligence in computer-aided diagnosis, biological image analysis, and computer-aided surgery and therapy.
目次
Brain Disease Classification and Progression using Machine Learning Techniques.- The Role of Content-Based Image Retrieval in Mammography CAD.- A Novel Image-based Approach for Early Detection of Prostate Cancer using DCE-MRI.- Computational Intelligent Image Analysis for Assisting Radiation Oncologists' Decision Making in Radiation Treatment Planning.- Computational Anatomy in the Abdomen: Automated Multi-Organ and Tumor Analysis from Computed Tomography.- Liver Volumetry in MRI by using Fast Marching Algorithm Coupled with 3D Geodesic Active Contour Segmentation.- Computer-aided Image Analysis for Vertebral Anatomy on X-ray CT Images.- Robust Segmentation of Challenging Lungs in CT using Multi-Stage Learning and Level Set Optimization.- Bone Suppression in Chest Radiographs by Means of Anatomically Specific Multiple Massive-Training ANNs Combined with Total Variation Minimization Smoothing and Consistency Processing.- Image Segmentation for Connectomics using Machine Learning.- Image Analysis Techniques for the Quantification of Brain Tumors on MR Images.- Respiratory and Cardiac Function Analysis on the Basis of Dynamic Chest Radiography.- Adaptive Noise Reduction and Edge Enhancement in Medical Images by using ICA.- Subtraction Techniques for CT and DSA and Automated Detection of Lung Nodules in 3D CT.
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