Scene segmentation techniques for the analysis of routine bone marrow smears from acute lymphoblastic leukemia patients.

Automated analysis of lymphoblast cell morphology is being evaluated as a basis for predicting the response to therapy of patients with acute lymphoblastic leukemia. A new technique of scene segmentation particularly applicable to the "cluttered" images of cells in routine bone marrow smears is described. Morphologic characteristics of lymphoblasts found in bone marrow smears made at time of diagnosis were measured by an automated, interactive image-processing system using the new scene segmentation technique.

Computer-aided medical decision making in radiotherapy.

Radiotherapy departments are becoming sophisticated in working with computers for isodose computations, treatment machine verifications and administrative and medical records. The next step lies in computer-assisted medical decision making. The logic for a patient's diagnostic work-up and treatment protocol can be stored in a computer.

The computer-assisted morphological classification of acute leukemia. I. Preliminary results.

The morphology of leukemic lymphoblasts, as seen in the initial routine bone marrow aspirate, of 40 children with ALL has been evaluated using a computer-assisted automated microscope. A statistic, derived from a combination of the number of macrolymphoblasts and the percentage of cells with no cytoplasm was found to predict response to standard therapy and to identify patients with a high probability of long-term remission as well as a group with a relatively poor response to therapy.