Debdoot Sheet

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This paper proposes a novel modification of the brightness preserving dynamic histogram equalization technique to improve its brightness preserving and contrast enhancement abilities while reducing its computational complexity. The modified technique, called Brightness Preserving Dynamic Fuzzy Histogram Equalization (BPDFHE), uses fuzzy statistics of(More)
Vision impairment due to pathological damage of the retina can largely be prevented through periodic screening using fundus color imaging. However the challenge with large scale screening is the inability to exhaustively detect fine blood vessels crucial to disease diagnosis. In this work we present a computational imaging framework using deep and ensemble(More)
Vision impairment due to pathological damage of the retina can largely be prevented through periodic screening using fundus color imaging. However the challenge with large-scale screening is the inability to exhaustively detect fine blood vessels crucial to disease diagnosis. In this work we present a computational imaging framework using deep and ensemble(More)
The objective of this work is to evaluate the performance of a set of despeckle filters for Optical Coherence Tomography (OCT) of the skin. The six filters are based on local statistics, median filtering, pixel homogeneity, geometric filtering and transformed domain homomorphic filtering. The results of this study suggest that geometric filtering algorithm(More)
Optical coherence tomography (OCT) is used for non-invasive diagnosis of diabetic macular edema assessing the retinal layers. In this paper, we propose a new fully convolutional deep architecture, termed ReLayNet, for end-to-end segmentation of retinal layers and fluid masses in eye OCT scans. ReLayNet uses a contracting path of convolutional blocks(More)
Optical coherence tomography (OCT) relies on speckle image formation by coherent sensing of photons diffracted from a broadband laser source incident on tissues. Its non-ionizing nature and tissue specific speckle appearance has leveraged rapid clinical translation for non-invasive high-resolution in situ imaging of critical organs and tissue viz. coronary(More)
Loss of visual acuity on account of retina-related vision impairment can be partly prevented through periodic screening with fundus color imaging. Largescale screening is currently challenged by inability to exhaustively detect fine blood vessels crucial to disease diagnosis. In this work we present a framework for reliable blood vessel detection in fundus(More)
Domain adaptation deals with adapting behaviour of machine learning based systems trained using samples in source domain to their deployment in target domain where the statistics of samples in both domains are dissimilar The task of directly training or adapting a learner in the target domain is challenged by lack of abundant labeled samples. In this paper(More)
Oral cancer evolves from different premalignant conditions and the key to save lives is through diagnosis of early symptoms. The conventional practice of post biopsy histopathology reporting is dependent on specificity of sampling site and optical coherence tomography (OCT) imaging is clinically used for guidance. Clinicians infer the tissue constitution by(More)
Overlapping of cervical cells and poor contrast of cell cytoplasm are the major issues in accurate detection and segmentation of cervical cells. An unsupervised cell segmentation approach is presented here. Cell clump segmentation was carried out using the extended depth of field (EDF) image created from the images of different focal planes. A modified Otsu(More)