The importance of partial voluming in multi-dimensional medical image segmentation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2208, Issue , 2001, Pages 1293-1294

  Pokrić, Maja ^a   Thacker, Neil ^a   Scott, Marietta L J ^a   Jackson, Alan ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION THEORY; HISTOLOGY; ITERATIVE METHODS; MEDICAL COMPUTING; MEDICAL IMAGE PROCESSING; MEDICAL IMAGING; SPECTROSCOPY; TISSUE;

EXPECTATION-MAXIMISATION; MULTI DIMENSIONAL; MULTI-DIMENSIONAL MODEL; MULTISPECTRAL IMAGES; OPTIMISATION TECHNIQUES; PARTIAL VOLUMES; PARTIAL VOLUMING; PROBABILITY MAPS;

IMAGE SEGMENTATION;

EID: 34047100929     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45468-3_200     Document Type: Conference Paper

References (3)

1. Laidlaw, D.H., Fleischer, K.W., Barr, A.H.: Partial-volume Bayesian Classification of Material Mixtures in MR Volume Data Using Voxel Histograms. IEEE Trans. Med. Imag. 17(1) (1998) 74-86
2. Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum Likelihood from Incomplete Data via EM Algorithm. Journal of the Royal Society 39 (1977) 1-38
3. Guillemaud, R., Brady, J.M.: Estimating the bias Field of MR Images. IEEE TRANS. on Medical Imaging 16(3) (1997) 238-251