Nuclear shape analysis has predicted outcome better than histologic grading in patients with clinically localized prostatic carcinoma. However, the requirement for manual nuclear contour tracing makes the method tedious and slow. Currently available image analysis system for nuclear shape analysis using light-absorption microscopy provide nuclear boundaries of insufficient clarity for automatic segmentation. We improved image resolution using confocal laser scanning microscopy, automatically detected nuclear boundaries by a multiscale segmentation algorithm and discriminated artifacts in a semiautomated way. A manual quantitative morphometry system and our semiautomated system distinguished eight cases of prostatic carcinoma from seven cases of benign prostatic hyperplasia by nuclear roundness factor, ellipticity, nuclear area and perimeter. The ease of semiautomated nuclear shape analysis should allow evaluation of large numbers of patients with known outcomes after treatment for clinically localized prostatic carcinoma to determine whether nuclear shape analysis can be extended from research to clinical usage.