HEp-2 Specimen Image Segmentation and Classification Using Very Deep Fully Convolutional Network

IEEE Transactions on Medical Imaging

Volumn 36, Issue 7, 2017, Pages 1561-1572

  Li, Yuexiang ^a   Shen, Linlin ^a   Yu, Shiqi ^a  

^a SHENZHEN UNIVERSITY   (China)

Author keywords

Cell patterns; classification; fully convolutional network; segmentation

Indexed keywords

CELL MEMBRANES; CLASSIFICATION (OF INFORMATION); CONVOLUTION; DIAGNOSIS; IMAGE CLASSIFICATION; PATTERN RECOGNITION; PATTERN RECOGNITION SYSTEMS; SEMANTICS;

AUTOIMMUNE DISEASE; AUTOMATIC PATTERN RECOGNITION; CELL PATTERNS; CONVOLUTIONAL NETWORKS; INTEROBSERVER VARIABILITY; SEGMENTATION ACCURACY; SEMANTIC SEGMENTATION; TRADITIONAL APPROACHES;

IMAGE SEGMENTATION;

AUTOMATED PATTERN RECOGNITION; CELL LINE; HUMAN; IMAGE PROCESSING; OBSERVER VARIATION;

CELL LINE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; OBSERVER VARIATION; PATTERN RECOGNITION, AUTOMATED;

EID: 85028407444     PISSN: 02780062     EISSN: 1558254X     Source Type: Journal    
DOI: 10.1109/TMI.2017.2672702     Document Type: Article

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