Patch-Level Nuclear Pleomorphism Scoring Using Convolutional Neural Networks

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dc.contributor.authorIheme, Leonardo O.
dc.contributor.authorSolmaz, Gizem
dc.contributor.authorTokat, Fatma
dc.contributor.authorCayir, Sercan
dc.contributor.authorBozaba, Engin
dc.contributor.authorYazici, Cisem
dc.contributor.authorOzsoy, Gulsah
dc.contributor.authorAyalti, Samet
dc.contributor.authorKayhan, Cavit Kerem
dc.contributor.authorInce, Umit
dc.date.accessioned2025-10-16T15:20:01Z
dc.date.issued2021
dc.description.abstract19th International Conference on Computer Analysis of Images and Patterns (CAIP), ELECTR NETWORK, SEP 28-30, 2021
dc.identifier.doi10.1007/978-3-030-89128-2\_18
dc.identifier.otherWOS:001160227400018
dc.identifier.urihttps://openaccess.acibadem.edu.tr/handle/11443/7447
dc.publisherSPRINGER INTERNATIONAL PUBLISHING AG
dc.sourceCOMPUTER ANALYSIS OF IMAGES AND PATTERNS, CAIP 2021, PT 1
dc.subjectCancer
dc.subjectNuclear pleomorhism
dc.subjectDeep learning
dc.subjectClassification
dc.subjectHistopathology
dc.titlePatch-Level Nuclear Pleomorphism Scoring Using Convolutional Neural Networks
dc.typeProceedings Paper

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