A circumscribing active contour model for delineation of nuclei and membranes of megakaryocytes in bone marrow trephine biopsy images

Dual-Channel Active Contour Model for Megakaryocytic Cell Segmentation in Bone Marrow Trephine Histology Images

“…We compare our MK nuclei detection method with an automatic unsupervised MK detection framework [42], [43], which we implement in Matlab, and the supervised MK nuclei detection method previously proposed in [44], which uses an Adaboost classifier to generate the cytoplasm mask. We use 50 bone marrow trephine images, including 73 megakaryocytes, of early-stage ET and PMF diseases in this evaluation; 50% of the images are used for training and 50% for testing.…”

“…First we evaluate the delineation accuracy of MK nuclei against other supervised and unsupervised methods. Second, we evaluate the accuracy of our DCAC model in segmenting the corresponding cytoplasmic regions against the CV model, the LBF model, our previously proposed circumscribing active contour (CAC) model [44], and the multi-region active contour model in [41]. We show that our framework is capable of delineating MKs very accurately.…”