Sonal Kothari

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Despite many efforts, regulation of skin and hair pigmentation is still not fully understood. This article focuses mainly on controversial aspects in pigment cell biology which have emerged over the last decade. The central role of tyrosinase as the key enzyme in initiation of melanogenesis has been closely associated with the 6BH4 dependent phenylalanine(More)
We propose an automatic color segmentation system that (1) incorporates domain knowledge to guide histological image segmentation and (2) normalizes images to reduce sensitivity to batch effects. Color segmentation is an important, yet difficult, component of image-based diagnostic systems. User-interactive guidance by domain experts—i.e.,(More)
This paper presents a novel, fast and semi-automatic method for accurate cell cluster segmentation and cell counting of digital tissue image samples. In pathological conditions, complex cell clusters are a prominent feature in tissue samples. Segmentation of these clusters is a major challenge for development of an accurate cell counting methodology. We(More)
OBJECTIVES With the objective of bringing clinical decision support systems to reality, this article reviews histopathological whole-slide imaging informatics methods, associated challenges, and future research opportunities. TARGET AUDIENCE This review targets pathologists and informaticians who have a limited understanding of the key aspects of(More)
BACKGROUND Automatic cancer diagnostic systems based on histological image classification are important for improving therapeutic decisions. Previous studies propose textural and morphological features for such systems. These features capture patterns in histological images that are useful for both cancer grading and subtyping. However, because many of(More)
Epidermal phenylalanine hydroxylase (PAH) produces L-tyrosine from the essential amino acid L-phenylalanine supporting melanogenesis in human melanocytes. Those PAH activities increase linearly in the different skin phototypes I-VI (Fitzpatrick classification) and also increase up to 24h after UVB light with only one minimal erythemal dose. Since UVB(More)
Computer-aided histological image classification systems are important for making objective and timely cancer diagnostic decisions. These systems use combinations of image features that quantify a variety of image properties. Because researchers tend to validate their diagnostic systems on specific cancer endpoints, it is difficult to predict which image(More)
We propose a framework for studying visual morphological patterns across histopathological whole-slide images (WSIs). Image representation is an important component of computer-aided decision support systems for histopathological cancer diagnosis. Such systems extract hundreds of quantitative image features from digitized tissue biopsy slides and produce(More)
This paper presents a fast methodology for the estimation of informative cell features from densely clustered RGB tissue images. The features estimated include nuclei count, nuclei size distribution, nuclei eccentricity (roundness) distribution, nuclei closeness distribution and cluster size distribution. Our methodology is a three step technique. Firstly,(More)