Deep Learning and Convolutional Neural Networks for Medical Image Computing (Record no. 205403)

MARC details
000 -LEADER
fixed length control field 06358nam a22005655i 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783319429991
-- 978-3-319-42999-1
040 ## - CATALOGING SOURCE
Transcribing agency CUS
245 10 - TITLE STATEMENT
Title Deep Learning and Convolutional Neural Networks for Medical Image Computing
Sub title Precision Medicine, High Performance and Large-Scale Datasets /
Statement of responsibility, etc. edited by Le Lu, Yefeng Zheng, Gustavo Carneiro, Lin Yang.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2017.
300 ## - DESCRIPTION
Extent XIII, 326 p. 117 illus., 100 illus. in color.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Part I: Review -- Chapter 1. Deep Learning and Computer-Aided Diagnosis for Medical Image Processing: A Personal Perspective -- Chapter 2. Review of Deep Learning Methods in Mammography, Cardiovascular and Microscopy Image Analysis -- Part II: Detection and Localization -- Chapter 3. Efficient False-Positive Reduction in Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation -- Chapter 4. Robust Landmark Detection in Volumetric Data with Efficient 3D Deep Learning -- Chapter 5. A Novel Cell Detection Method Using Deep Convolutional Neural Network and Maximum-Weight Independent Set -- Chapter 6. Deep Learning for Histopathological Image Analysis: Towards Computerized Diagnosis on Cancers -- Chapter 7. Interstitial Lung Diseases via Deep Convolutional Neural Networks: Segmentation Label Propagation, Unordered Pooling and Cross-Dataset Learning -- Chapter 8. Three Aspects on Using Convolutional Neural Networks for Computer-Aided Detection in Medical Imaging -- Chapter 9. Cell Detection with Deep Learning Accelerated by Sparse Kernel -- Chapter 10. Fully Convolutional Networks in Medical Imaging: Applications to Image Enhancement and Recognition -- Chapter 11. On the Necessity of Fine-Tuned Convolutional Neural Networks for Medical Imaging -- Part III: Segmentation -- Chapter 12. Fully Automated Segmentation Using Distance Regularized Level Set and Deep-Structured Learning and Inference -- Chapter 13. Combining Deep Learning and Structured Prediction for Segmenting Masses in Mammograms -- Chapter 14. Deep Learning Based Automatic Segmentation of Pathological Kidney in CT: Local vs. Global Image Context -- Chapter 15. Robust Cell Detection and Segmentation in Histopathological Images using Sparse Reconstruction and Stacked Denoising Autoencoders -- Chapter 16. Automatic Pancreas Segmentation Using Coarse-to-Fine Superpixel Labeling -- Part IV: Big Dataset and Text-Image Deep Mining -- Chapter 17. Interleaved Text/Image Deep Mining on a Large-Scale Radiology Image Database.
650 #0 - SUBJECT
Keyword Optical data processing.
650 #0 - SUBJECT
Keyword Artificial intelligence.
650 #0 - SUBJECT
Keyword Neural networks (Computer science) .
650 #0 - SUBJECT
Keyword Radiology.
650 14 - SUBJECT
Keyword Image Processing and Computer Vision.
650 24 - SUBJECT
Keyword Artificial Intelligence.
650 24 - SUBJECT
Keyword Mathematical Models of Cognitive Processes and Neural Networks.
650 24 - SUBJECT
Keyword Imaging / Radiology.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Lu, Le.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Zheng, Yefeng.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Carneiro, Gustavo.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Yang, Lin.
856 40 - ONLINE RESOURCES
url https://doi.org/10.1007/978-3-319-42999-1
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type e-Books
700 1# - ADDED ENTRY--PERSONAL NAME
-- https://orcid.org/0000-0002-5571-6220
912 ## -
-- ZDB-2-SCS
912 ## -
-- ZDB-2-SXCS
Holdings
Home library Current library Full call number Accession number Koha item type
Central Library, Sikkim University Central Library, Sikkim University 006.6 E-2987 e-Books
SIKKIM UNIVERSITY
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