Improving early recognition of malignant melanomas by digital image analysis in dermatoscopy.

The malignant melanoma (MM) is the most dangerous human skin disease. The incidence increased dramatically during the last years. The only chance for the patient is an early recognition and excision of the MM.

Improvement of monitoring of melanocytic skin lesions with the use of a computerized acquisition and surveillance unit with a skin surface microscopic television camera.

Background: Photographic documentation of melanocytic skin lesions is important. Storage and retrieval of slides, however, take much time and space.

Objective: Our purpose was to develop and clinically test a computerized acquisition and surveillance (CAS) unit with a television camera for monitoring including measurements of lesional areas.

Multivariate DNA cytometry discriminates between Spitz nevi and malignant melanomas because large polymorphic nuclei in Spitz nevi are not aneuploid.

To elucidate the reasons for the malignant histologic appearance of melanocytic nuclei within benign Spitz nevi (SN), we evaluated nuclear DNA distribution and nuclear size using a computerized image analysis system. In each case of 28 SN and 34 malignant melanomas (MM), about 100 randomly sampled nuclei were analyzed, prepared as monolayers from paraffin-embedded tissues. Large nuclei in MM (nuclear area > mean nuclear area of normal melanocytes + 4 delta) were significantly more likely to be aneuploid (DNA content > or = 5c) than large nuclei in SN chi2 test, p < 0.

Clinical applications of Bayesian belief networks in pathology.

Bayesian belief networks (BBNs) are a novel tool for representing knowledge about diagnostic decision making and for obtaining a numerical measure of certainty in the final diagnosis. Belief networks have been applied to the pathological assessment of breast, prostate and skin lesions and have been shown to provide consistency in the grading of microscopic features and improve diagnosis. These applications are reviewed in the current paper.

Evaluation of different image acquisition techniques for a computer vision system in the diagnosis of malignant melanoma.

Background: Digital image analysis was found to be a useful technique for improved accuracy of preoperative diagnosis of melanocytic lesions. In previous studies digitized color slides were used as input for digital image analysis. New technologies and smaller video cameras made it possible to develop a camera system that allows the digitization of skin lesions directly from the patient.