On a relaxation-labelling algorithm for quantitative assessment of tumour vasculature in tissue section images.
Although tumour vasculature constitutes a biological factor playing a crucial role in the radiation response of tumours, the current procedures of assessment are semiquantitative, typically employing visual examination of stained histological material. Such techniques are also time consuming, and inefficient of extracting essential information on the vascular network. Image analysis has yet to contribute significantly in this direction, and most studies to date focus on blood vessel segmentation through empirical, user-selected thresholds. The present paper proposes an alternative segmentation approach, based on a probabilistic relaxation algorithm, applied in microscopic images of stained tissues. After image partitioning various information is obtained, such as vascular domains and geometrical characteristics of vessels.
Loukas
Constantinos G
CG
Gray Cancer Institute, P.O. Box 100, Mount Vernon Hospital, Northwood, Middlesex HA6 2JR, UK. c.loukas@ion.ucl.ac.uk
Linney
Alf
A
D000465:Algorithms; D002295:Carcinoma, Transitional Cell / Q000098:blood supply* / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007150:Immunohistochemistry; D009389:Neovascularization, Pathologic; D012680:Sensitivity and Specificity; D001749:Urinary Bladder Neoplasms / Q000098:blood supply* / Q000473:pathology