A computationally efficient approach to the estimation of two- and three-dimensional hidden Markov models

IEEE Transactions on Image Processing

Volumn 15, Issue 7, 2006, Pages 1871-1886

  Joshi, Dhiraj ^a   Li, Jia ^b   Wang, James Z ^a  

^a The Pennsylvania State University   (United States)

^b PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Hidden Markov models (HMMs); Maximum likelihood estimation; Parameter estimation; Three dimensional (3 D) HMM; Viterbi training; Volume image processing

Indexed keywords

ALGORITHMS; IMAGE ANALYSIS; MARKOV PROCESSES; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; PARAMETER ESTIMATION;

HIDDEN MARKOV MODELS (HMMS); VITERBI TRAINING; VOLUME IMAGE PROCESSING;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; PROBABILITY; SIGNAL PROCESSING; STATISTICAL MODEL; STATISTICS; THREE DIMENSIONAL IMAGING;

ALGORITHMS; COMPUTER GRAPHICS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; MARKOV CHAINS; MODELS, STATISTICAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; SIGNAL PROCESSING, COMPUTER-ASSISTED; STOCHASTIC PROCESSES;

EID: 33745590884     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2006.877039     Document Type: Article

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