Few algorithms for histopathological images in computational pathology

dc.contributor.guideSethi, Amit
dc.coverage.spatialElectronics and Electrical Engineering
dc.creator.researcherVahadane, Abhishek
dc.date.accessioned2023-04-21T06:30:17Z
dc.date.available2023-04-21T06:30:17Z
dc.date.awarded2017
dc.date.completed2017
dc.date.registered2011
dc.description.abstractIn computational pathology huge stacks of histological data are made available through advances in the microscopic image acquisition Clinicians cannot learn easily from this big data due to obvious human limitations However machine learning systems can learn important patterns from these huge histological data to improve the diagnosis and prognosis Such automated prediction can act as a second opinion for the experts to help make their decisions In this thesis we address four different pr
dc.description.noteNot Available
dc.format.accompanyingmaterialNone
dc.format.dimensionsNot Available
dc.format.extentNot Available
dc.identifier.urihttp://hdl.handle.net/10603/478387
dc.languageEnglish
dc.publisher.institutionDEPARTMENT OF ELECTRONICS AND ELECTRICAL ENGINEERING
dc.publisher.placeGuwahati
dc.publisher.universityIndian Institute of Technology Guwahati
dc.relationNot Available
dc.rightsself
dc.source.universityUniversity
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Electrical and Electronic
dc.titleFew algorithms for histopathological images in computational pathology
dc.title.alternativeNot available
dc.type.degreePh.D.

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