An approach for contour detection of human kidneys from ultrasound images using Markov random fields and active contours

Medical Image Analysis

Volumn 9, Issue 1, 2005, Pages 1-23

  Martín Fernández, Marcos ^a   Alberola López, Carlos ^a  

^a UNIVERSITY OF VALLADOLID   (Spain)

Author keywords

Active contours; Bayesian segmentation; Deformation model; Markov random fields; US

Indexed keywords

BIOLOGICAL ORGANS; PROBABILITY DISTRIBUTIONS; RANDOM PROCESSES; SENSITIVITY ANALYSIS; ULTRASONICS;

BAYESIAN METHOD; ECHOGRAPHY; KIDNEY CONTOURS;

MEDICAL IMAGING;

ACCURACY; ARTICLE; BAYES THEOREM; COMPUTER ASSISTED TOMOGRAPHY; ECHOGRAPHY; HUMAN; IMAGE QUALITY; INTERFEROMETRY; KIDNEY; MATHEMATICAL COMPUTING; NONHUMAN; PRIORITY JOURNAL; PROBABILITY; SENSITIVITY ANALYSIS; THREE DIMENSIONAL IMAGING;

BAYES THEOREM; HUMANS; KIDNEY; MAGNETIC RESONANCE IMAGING; MARKOV CHAINS; MODELS, THEORETICAL; RANDOM ALLOCATION; SENSITIVITY AND SPECIFICITY;

EID: 10844286394     PISSN: 13618415     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.media.2004.05.001     Document Type: Article

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