Sumit Kumar Nath

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Quantifying the behavior of cells individually, and in clusters as part of a population, under a range of experimental conditions, is a challenging computational task with many biological applications. We propose a versatile algorithm for segmentation and tracking of multiple motile epithelial cells during wound healing using time-lapse video. The(More)
Current level-set based approaches for segmenting a large number of objects are computationally expensive since they require a unique level set per object (the N-level set paradigm), or [log2N] level sets when using a multiphase interface tracking formulation. Incorporating energy-based coupling constraints to control the topological interactions between(More)
AIMS To investigate the use of a computer-assisted technology for objective, cell-based quantification of molecular biomarkers in specified cell types in histopathology specimens, with the aim of advancing current visual estimation and pixel-level (rather than cell-based) quantification methods. METHODS AND RESULTS Tissue specimens were(More)
BACKGROUND AND DESIGN Vitiligo is a disorder whose cause is not well understood. This study was undertaken to clarify whether genetic factors are involved in the pathogenesis of vitiligo. Data on 160 white kindreds living in the United States have been collected. Each family was ascertained through a proband afflicted with vitiligo. The nature and extent of(More)
Vitiligo is a dermatological disorder characterized by hypopigmentary patches that tend to become progressive over time. There are reports of extensive familial aggregation. A genetic model for this disorder was earlier proposed by us. This model postulates that recessive alleles at multiple unlinked autosomal loci interact epistatically in the pathogenesis(More)
This paper makes new contributions in motion detection, object segmentation and trajectory estimation to create a successful object tracking system. A new efficient motion detection algorithm referred to as the flux tensor is used to detect moving objects in infrared video without requiring background modeling or contour extraction. The flux tensor-based(More)
With the increasing availability of live cell imaging technology, tracking cells and other moving objects in live cell videos has become a major challenge for bioimage informatics. An inherent problem for most cell tracking algorithms is over- or under-segmentation of cells – many algorithms tend to recognize one cell as several cells or vice versa. We(More)
Understanding behavior of migrating cells is becoming an emerging research area with many important applications. Segmentation and tracking constitute vital steps of this research. In this paper, we present an automated cell segmentation and tracking system designed to study migration of cells imaged with a phase contrast microscope. For segmentation the(More)
Persistent object tracking in complex and adverse environments can be improved by fusing information from multiple sensors and sources. We present a new moving object detection and tracking system that robustly fuses infrared and visible video within a level set framework. We also introduce the concept of the flux tensor as a generalization of the 3D(More)