Computer aided image segmentation and classification for viable and non-viable tumor identification in osteosarcoma

Pacific Symposium on Biocomputing

Volumn 0, Issue 212679, 2017, Pages 195-206

  Arunachalam, Harish Babu ^a   Mishra, Rashika ^a   Armaselu, Bogdan ^a   Daescu, Ovidiu ^a   Martinez, Maria ^a   Leavey, Patrick ^b   Rakheja, Dinesh ^b   Cederberg, Kevin ^b   Sengupta, Anita ^b   Ni’Suilleabhain, Molly ^b  

^a The University of Texas at Dallas   (United States)

^b UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

Author keywords

Image segmentation; Osteosarcoma; Otsu thresholding; SVS image analysis

Indexed keywords

DISEASES; IMAGE ANALYSIS; IMAGE CLASSIFICATION; PATIENT TREATMENT; PIXELS; TUMORS;

DIGITAL IMAGE ANALYSIS; HIGH RESOLUTION IMAGE; INTEROBSERVER VARIABILITY; K-MEANS CLUSTERING TECHNIQUES; MAGNIFICATION FACTORS; OSTEOSARCOMA; OTSU THRESHOLDING; SEGMENTATION TECHNIQUES;

IMAGE SEGMENTATION;

ALGORITHM; BIOLOGY; BONE TUMOR; CHILD; CLUSTER ANALYSIS; COLOR; COMPUTER ASSISTED DIAGNOSIS; DIAGNOSTIC IMAGING; FIBROSIS; HUMAN; NECROSIS; OSTEOSARCOMA; PATHOLOGY; PROCEDURES; SOFTWARE;

ALGORITHMS; BONE NEOPLASMS; CHILD; CLUSTER ANALYSIS; COLOR; COMPUTATIONAL BIOLOGY; FIBROSIS; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; NECROSIS; OSTEOSARCOMA; SOFTWARE;

EID: 85020745978     PISSN: 23356928     EISSN: 23356936     Source Type: Journal    
DOI: 10.1142/9789813207813_0020     Document Type: Conference Paper

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