{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"Cancer Diagnosis and Prognosis with Histopathology Image Analysis and Pattern Recognition","metadata":[{"label":"dc.identifier.uri","value":"http://hdl.handle.net/11401/78320"},{"label":"dcterms.abstract","value":"The dissertation focuses on the histopathology image analysis for cancer     diagnosis and prognosis, based on the innovation of histopathological machine     vision techniques. Histopathology images are regarded as the reference     standard to identify diseases, and especially as a gold standard on cancer diagnosis. With the recent advance of the electronic scanners, digitized whole     slide images (WSI) make it possible to analyze cancer tissues in high resolution     and large-scale manner. At the same time, computer aided diagnosis (CAD) algorithms are being developed to detect cancer automatically, both in radiological and pathological field. However, those CAD algorithms are     based on object segmentation and handcrafted features, which are not fully     automatic. I developed innovative methods and frameworks to assist cancer     diagnosis and prognosis automatically, without sophisticated feature extraction.     The major projects are intermediate prostate cancer grading, cell nuclei     segmentation using deep learning and nuclei segmentation evaluation through     image synthesis. My research novelties include multi-resolution histopathology     image analysis, fully automatic gland cancerous degree classification, and     nuclei segmentation and synthesis using deep learning."},{"label":"dcterms.available","value":"2020-04-03"},{"label":"dcterms.contributor","value":"Advisors: Huang, Chuan; Vaska, Paul; Jia, Shu; Zhu, Wei"},{"label":"dcterms.creator","value":"Zhou, Naiyun"},{"label":"dcterms.date","value":"2017"},{"label":"dcterms.dateAccepted","value":"2018-07-03T17:54:10Z"},{"label":"dcterms.dateSubmitted","value":"2018-07-03T17:54:10Z"},{"label":"dcterms.description","value":"Dissertation"},{"label":"dcterms.extent","value":"128 pages"},{"label":"dcterms.format","value":"application/pdf"},{"label":"dcterms.identifier","value":"http://hdl.handle.net/11401/78320"},{"label":"dcterms.issued","value":"2017-12-01"},{"label":"dcterms.language","value":"en"},{"label":"dcterms.provenance","value":"Submitted by Jason Torre (fjason.torre@stonybrook.edu) on 2018-07-03T17:54:10Z\nNo. of bitstreams: 1\nZhou_grad.sunysb_0771E_13529.pdf: 3622846 bytes, checksum: ed4ccb2eefba38c8a98e1d7a2b0795e2 (MD5)"},{"label":"dcterms.publisher","value":"Stony Brook University"},{"label":"dcterms.subject","value":"Biomedical engineering"},{"label":"dcterms.title","value":"Cancer Diagnosis and Prognosis with Histopathology Image Analysis and Pattern Recognition"},{"label":"dcterms.type","value":"Text"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/11%2F96%2F92%2F119692777604423213119269367678601874139/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/11%2F96%2F92%2F119692777604423213119269367678601874139","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}