Cutting out the middleman: Measuring nuclear area in histopathology slides without segmentation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9901 LNCS, Issue , 2016, Pages 632-639

  Veta, Mitko ^a   Van Diest, Paul J ^b   Pluim, Josien P W ^a  

^a EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

Author keywords

Breast cancer; Convolutional neural networks; Deep learning; Histopathology image analysis

Indexed keywords

CONVOLUTION; DEEP LEARNING; DEEP NEURAL NETWORKS; DISEASES; GRADING; IMAGE SEGMENTATION; NEURAL NETWORKS; TUMORS;

BREAST CANCER; BREAST CANCER GRADING; CONVOLUTIONAL NEURAL NETWORK; DEEP CONVOLUTIONAL NEURAL NETWORKS; MACHINE LEARNING MODELS; NUCLEI DETECTIONS; NUCLEI SEGMENTATION; REGION STATISTICS;

MEDICAL IMAGING;

EID: 84996565667     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-46723-8_73     Document Type: Conference Paper

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