Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.
You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.
After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.
Presents computational intelligence technology uses in medical image analysis
Examines medical decision making based on biomedical images
Covers the state-of-the-art research and technologies in computational intelligence in medical decision making
This book provides 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.
Content Level »Research
Keywords »artificial neural networks - biomedical imaging - computational intelligence - computer-aided diagnosis - computer-aided surgery - computerized medical support - machine learning - medical decision making - medical image analysis - medical informatics - support vector machines
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.