Combined image-processing algorithms for improved optical coherence tomography of prostate nerves

Journal of Biomedical Optics

Volumn 15, Issue 4, 2010, Pages

  Chitchian, Shahab ^a   Weldon, Thomas P ^b   Fiddy, Michael A ^a   Fried, Nathaniel M ^c  

^a UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE   (United States)

^b University of North Carolina at Charlotte   (United States)

^c DEPARTMENT OF PATHOLOGY   (United States)

Author keywords

Cavernous nerve; Optical coherence tomography; Prostate cancer; Prostate gland

Indexed keywords

AUTOMATIC IDENTIFICATION; CAVERNOUS NERVE; DE-NOISING; DE-NOISING ALGORITHM; DUAL-TREE COMPLEX WAVELET TRANSFORM; EDGE DETECTION ALGORITHMS; IMAGE-PROCESSING ALGORITHMS; IMAGING DEPTH; NOISE RATIO; PROSTATE CANCERS; PROSTATE GLANDS; SPECKLE NOISE; TIME DOMAIN;

ADAPTIVE ALGORITHMS; AUTOMATION; DISEASES; IMAGE SEGMENTATION; NOISE POLLUTION CONTROL; SURGERY; TOMOGRAPHY; TREES (MATHEMATICS); WAVELET TRANSFORMS;

EDGE DETECTION;

RATTUS;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; INNERVATION; MALE; METHODOLOGY; OPTICAL COHERENCE TOMOGRAPHY; PERIPHERAL NERVE; PROSTATE; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MALE; PATTERN RECOGNITION, AUTOMATED; PERIPHERAL NERVES; PROSTATE; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, OPTICAL COHERENCE;

EID: 79952199169     PISSN: 10833668     EISSN: 15602281     Source Type: Journal    
DOI: 10.1117/1.3481144     Document Type: Article

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