GyneScan: An improved online paradigm for screening of ovarian cancer via tissue characterization

Technology in Cancer Research and Treatment

Volumn 13, Issue 6, 2014, Pages 529-540

  Rajendra Acharya, U ^a   Vinitha Sree, S ^b   Kulshreshtha, Sanjeev ^b   Molinari, Filippo ^c   Koh, Joel En Wei ^a   Saba, Luca ^d,e   Suri, Jasjit S ^f,g,h  

^a DEPARTMENT OF ELECTRONICS AND COMPUTER ENGINEERING   (Singapore)

^b Global Biomedical Technologies   (United States)

^c POLITECNICO DI TORINO   (Italy)

^d Vascular Screening and Diagnostic Centre   (United Kingdom)

^e UNIVERSITY OF CYPRUS   (Cyprus)

^f Global Biomedical Technologies   (United States)

^g AtheroPoint   (United States)

^h Nucl Eng Idaho State University   (United States)

Author keywords

Classification; Computer aided diagnosis; Feature extraction; Ovarian cancer; Screening; Texture analysis; Tissue characterization; Ultrasound

Indexed keywords

ACCURACY; ADULT; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYESIAN LEARNING; CANCER SCINTISCANNING; CANCER SCREENING; CLINICAL ARTICLE; CONCEPTUAL FRAMEWORK; DECISION TREE; ECHOGRAPHY; FEMALE; GENETIC ALGORITHM; GYNESCAN; HUMAN; K NEAREST NEIGHBOR; OVARY CANCER; PREDICTIVE VALUE; PROBABILITY; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; TISSUE CHARACTERIZATION; ALGORITHM; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; MIDDLE AGED; OVARIAN NEOPLASMS; PATHOLOGY; REPRODUCIBILITY; WEB BROWSER;

ADULT; AGED; ALGORITHMS; DECISION TREES; DIAGNOSIS, COMPUTER-ASSISTED; FEMALE; HUMANS; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); OVARIAN NEOPLASMS; REPRODUCIBILITY OF RESULTS; SOFTWARE; SUPPORT VECTOR MACHINES; WEB BROWSER;

EID: 84904369088     PISSN: 15330346     EISSN: None     Source Type: Journal    
DOI: 10.7785/tcrtexpress.2013.600273     Document Type: Article

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