The watershed transform in pathological image analysis: application in rectiulocyte count from supravital stained smears

Background: Morphometric studies based on image analysis are a useful adjunct for quantitative analysis of microscopic images. However, effective separation of overlapping objects if often the bottleneck in image analysis techniques. We employ the watershed transform for counting reticulocytes from images of supravitally stained smears.Methods: The algorithm was developed with the Python programming platform, using the Numpy, Scipy and OpenCV libraries. The initial development and testing of the software were carried out with images from the American Society of Hematology Image Library. Then a pilot study with 30 samples was then taken up. The samples were incubated with supravital stain immediately after collection, and smears prepared. The smears were microphotographed at 100X objective, with no more than 150 RBCs per field. Reticulocyte count was carried out manually as well as by image analysis.Results: 600 out of 663 reticulocytes (90.49%) were correctly identified, with a specificity of 98%. The major difficulty faced was the slight bluish tinge seen in polychromatic RBCs, which were inconsistently detected by the software.Conclusions: The watershed transform can be used successfully to separate overlapping objects usually encountered in pathological smears. The algorithm has the potential to develop into a generalized cell classifier for cytopathology and hematology.

Automatic DTI-based parcellation of the corpus callosum through the watershed transform

INTRODUCTION: Parcellation of the corpus callosum (CC) in the midsagittal cross-section of the brain is of utmost importance for the study of diffusion properties within this structure. The complexity of this operation comes from the absence of macroscopic anatomical landmarks to help in dividing the CC into different callosal areas. In this paper we propose a completely automatic method for CC parcellation using diffusion tensor imaging (DTI). METHODS: A dataset of 15 diffusion MRI volumes from normal subjects was used. For each subject, the midsagital slice was automatically detected based on the Fractional Anisotropy (FA) map. Then, segmentation of the CC in the midsgital slice was performed using the hierarchical watershed transform over a weighted FA-map. Finally, parcellation of the CC was obtained through the application of the watershed transform from chosen markers. RESULTS: Parcellation results obtained were consistent for fourteen of the fifteen subjects tested. Results were similar to the ones obtained from tractography-based methods. Tractography confirmed that the cortical regions associated with each obtained CC region were consistent with the literature. CONCLUSIONS: A completely automatic DTI-based parcellation method for the CC was designed and presented. It is not based on tractography, which makes it fast and computationally inexpensive. While most of the existing methods for parcellation of the CC determine an average behavior for the subjects based on population studies, the proposed method reflects the diffusion properties specific for each subject. Parcellation boundaries are found based on the diffusion properties within each individual CC, which makes it more reliable and less affected by differences in size and shape among subjects.

Segmentation of Hippocampus in Human Brain MRI Using Watersnakes / 대한의료정보학회지

OBJECTIVE: The algorithm of Watersnakes is used to segment the hippocampus on one slice of MR image. METHODS: This method integrates the watershed transform and the active contour algorithm. The watershed transform, based on mathematical morphology, is powerful and flexible for segmentation. However, it does not allow the characteristics of region boundaries to be included into the way that active contour algorithm do. So, oversegmentation is in the result, even to hippocampus. For watersnakes algorithm, the primitive contour of hippocampus can be obtained using watershed transform. Based on energy-driven, the contour of hippocampus develops into the ultimate result. In the process of energy-driven, the information relating to characteristics of region boundaries is involved. RESULTS: The results of watersnakes showed oversegmentation could be avoided, compared to the results of watershed transform. CONCLUSION: Watersnakes can use the advantage of watershed transform and active contour algorithm to improve the results of segmentation.