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024 7 _a10.1007/978-981-13-8930-6
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082 0 4 _a621.382
_223
245 1 0 _aHybrid Machine Intelligence for Medical Image Analysis
_h[electronic resource] /
_cedited by Siddhartha Bhattacharyya, Debanjan Konar, Jan Platos, Chinmoy Kar, Kalpana Sharma.
250 _a1st ed. 2020.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2020.
300 _aXVI, 293 p. 179 illus., 114 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v841
505 0 _aPreface -- Introduction -- Brain Tumor Segmentation from T1 Weighted MRI Images Using Rough Set Reduct and Quantum Inspired Particle Swarm Optimization -- Automated Region of Interest detection of Magnetic Resonance (MR) images by Center of Gravity (CoG) -- Brain tumors detection through low level features detection and rotation estimation -- Automatic MRI Image Segmentation for Brain tumors detection using Multilevel Sigmoid Activation (MUSIG) function -- Automatic Segmentation of pulmonary nodules in CT Images for Lung Cancer detection using self-supervised Neural Network Architecture -- A Hierarchical Fused Fuzzy Deep Neural Network for MRI Image Segmentation and Brain Tumor Classification -- Computer Aided Detection of Mammographic Lesions using Convolutional Neural Network (CNN) -- Conclusion.
520 _aThe book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using convolutional neural networks.
650 0 _aSignal processing.
_94052
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer vision.
_936209
650 0 _aPattern recognition systems.
_93953
650 1 4 _aSignal, Speech and Image Processing .
_931566
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Vision.
_936210
650 2 4 _aAutomated Pattern Recognition.
_931568
700 1 _aBhattacharyya, Siddhartha.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_936211
700 1 _aKonar, Debanjan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_936212
700 1 _aPlatos, Jan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_936213
700 1 _aKar, Chinmoy.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_936214
700 1 _aSharma, Kalpana.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_936215
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
_z9789811389320
830 0 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v841
_936217
856 4 0 _uhttps://doi.org/10.1007/978-981-13-8930-6
912 _aZDB-2-ENG
912 _aZDB-2-SXE
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