English
norskBlar i forfatter "Somani, Ayush"
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Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-03-03)The quantitative analysis of subcellular organelles such as mitochondria in cell fluorescence microscopy images is a demanding task because of the inherent challenges in the segmentation of these small and morphologically diverse structures. In this article, we demonstrate the use of a machine learning-aided segmentation and analysis pipeline for the quantification of mitochondrial morphology in ... -
Counterfactual Explainable Gastrointestinal and Colonoscopy Image Segmentation
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-26)Segmenting medical images accurately and reliably is crucial for disease diagnosis and treatment. Due to the wide assortment of objects’ sizes, shapes, and scanning modalities, it has become more challenging. Many convolutional neural networks (CNN) have recently been designed for segmentation tasks and achieved great success. This paper presents an optimized deep learning solution using DeepLabv3+ ... -
Image Inpainting With Hypergraphs for Resolution Improvement in Scanning Acoustic Microscopy
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-14)Scanning Acoustic Microscopy (SAM) uses high-frequency acoustic waves to generate non-ionizing, label-free images of the surface and internal structures of industrial objects and biological specimens. The resolution of SAM images is limited by several factors such as the frequency of excitation signals, the signal-to-noise ratio, and the pixel size. We propose to use a hypergraphs image inpainting ... -
Image Inpainting With Hypergraphs for Resolution Improvement in Scanning Acoustic Microscopy
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-08-14)Scanning Acoustic Microscopy (SAM) uses high-frequency acoustic waves to generate non-ionizing, label-free images of the surface and internal structures of industrial objects and biological specimens. The resolution of SAM images is limited by several factors such as the frequency of excitation signals, the signal-to-noise ratio, and the pixel size. We propose to use a hypergraphs image inpainting ... -
Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-09-28)Mitochondria play a crucial role in cellular metabolism. This paper presents a novel method to visualize mitochondria in living cells without the use of fluorescent markers. We propose a physics-guided deep learning approach for obtaining virtually labeled micrographs of mitochondria from bright-field images. We integrate a microscope’s point spread function in the learning of an adversarial neural ...
