This thesis describes the development of: (i) an automatic chromosome analysis system capable of producing to a high degree of accuracy and consistency a correct classification for damaged chromosomes at a low cost and (ii) a parallel computer system to enable more rapid chromosome analysis. Chromosomes can be examined in a cytogenetics laboratory for a variety of purposes including an assessment of the affects of ionisation exposure on the genetic code of the cell. Scoring of chromosome aberrations caused by ionisation of radiation exposure, is possible by detecting dicentric chromosomes. In addition this approach provides a good biological radiation measure (dosimeter). However, currently manual methods are extremely time consuming and expensive with respect to labour costs. For the low radiation doses it is necessary to analyse a large number of chromosomes to identify a small number of damaged ones to score the number of aberrations. Consequently, the main objective of this research programme is to develop a rapid, low cost, and accurate automated chromosome analysis system. This research has concentrated solely on scoring dicentric chromosome since their characteristic shape is relatively easy to recognise in most cases and they most commonly created by exposure to radiation. The methods and theories considered in this thesis concerns chromosome image selection by automatic segment extraction using of the following: grey levels; image extraction by seed aggregation, a two dimensional function, a moment algorithm, for chromosome orientation; chromosome centreline determination; rapid detection of the chromosome centromere of the candidate. The new methods developed by the author and presented herein concern three steps or processes in automatic chromosome analysis. These include (i) a new segmentation scheme (ii) automatic selection the cell threshold grey scale level and (iii) the design a new methods capable of detecting bent chromosome with rapid determination the chromosome centromere. Parallel processing using the processor farm technique has been successfully developed to enable a more rapid chromosome classification system. The techniques described have been carefully tested and evaluated and have clearly demonstrated the potential application of the analysis methods by the author.