Machine Learning/Deep Learning in Medical Image Processing

Many recent studies on medical image processing have involved the use of machine learning (ML) and deep learning (DL). This special issue, “Machine Learning/Deep Learning in Medical Image Processing”, has been launched to provide an opportunity for researchers in the area of medical image processing...

Full description

Saved in:
Bibliographic Details
Sonstige:
Year of Publication:2021
Language:English
Physical Description:1 electronic resource (132 p.)
Tags: Add Tag
No Tags, Be the first to tag this record!
LEADER 02408nam-a2200649z--4500
001 993546285804498
005 20231214132827.0
006 m o d
007 cr|mn|---annan
008 202201s2021 xx |||||o ||| 0|eng d
035 |a (CKB)5400000000045473 
035 |a (oapen)https://directory.doabooks.org/handle/20.500.12854/77165 
035 |a (EXLCZ)995400000000045473 
041 0 |a eng 
100 1 |a Nishio, Mizuho  |4 edt 
245 1 0 |a Machine Learning/Deep Learning in Medical Image Processing 
260 |a Basel, Switzerland  |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2021 
300 |a 1 electronic resource (132 p.) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
520 |a Many recent studies on medical image processing have involved the use of machine learning (ML) and deep learning (DL). This special issue, “Machine Learning/Deep Learning in Medical Image Processing”, has been launched to provide an opportunity for researchers in the area of medical image processing to highlight recent developments made in their fields with ML/DL. Seven excellent papers that cover a wide variety of medical/clinical aspects are selected in this special issue. 
546 |a English 
650 7 |a Technology: general issues  |2 bicssc 
653 |a pancreas 
653 |a segmentation 
653 |a computed tomography 
653 |a deep learning 
653 |a data augmentation 
653 |a neoplasm metastasis 
653 |a ovarian neoplasms 
653 |a radiation exposure 
653 |a tomography 
653 |a x-ray computed 
653 |a prostate carcinoma 
653 |a microscopic 
653 |a convolutional neural network 
653 |a machine learning 
653 |a handcrafted 
653 |a oral carcinoma 
653 |a medical image segmentation 
653 |a colon cancer 
653 |a colon polyps 
653 |a OCT 
653 |a optical biopsy 
653 |a animal rat models 
653 |a CADx 
653 |a airway volume analysis 
653 |a artificial intelligence 
653 |a coronary artery disease 
653 |a SPECT MPI scans 
653 |a convolutional neural networks 
653 |a transfer learning 
653 |a classification models 
776 |z 3-0365-2664-1 
776 |z 3-0365-2665-X 
700 1 |a Nishio, Mizuho  |4 oth 
906 |a BOOK 
ADM |b 2023-12-15 05:32:27 Europe/Vienna  |f system  |c marc21  |a 2022-04-04 09:22:53 Europe/Vienna  |g false 
AVE |i DOAB Directory of Open Access Books  |P DOAB Directory of Open Access Books  |x https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5338158330004498&Force_direct=true  |Z 5338158330004498  |b Available  |8 5338158330004498