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.

A survey on histological image analysis-based assessment of three major biological factors influencing radiotherapy: proliferation, hypoxia and vasculature.

Image analysis is a rapidly evolving field with growing applications in science and engineering. In cancer research, it has played a key role in advancing techniques of major diagnostic importance, minimising human intervention and providing vital clinical information. Especially in the field of tissue microscopy, the use of computers for the automated analysis of histological sections is becoming increasingly important. This paper presents an overview of various image analysis methodologies and summarises developments in this field, with great emphasis given on the assessment of three major biological factors known to influence the outcome of radiotherapy: proliferation, vasculature and hypoxia. A brief introduction followed by a survey is provided in each of these areas.