Surya Prasath

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Assistant Professor

University of Cincinnati

United States

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About

Surya Prasath is an Assistant Professor at the University of Cincinnati, USA. His research focuses on advanced segmentation techniques in histopathology, hyperspectral image restoration, and the applications of deep learning in medical imaging. Recent articles include topics such as automated nuclei segmentation, glioma subtype classification, and prediction models for genetic mutations in histopathological imaging.

Recent Grants

Grant: Close

Leveraging Deep Learning to Delineate Histologic Features Predictive of Pediatric Ulcerative Colitis

Open Date: 2022-01-01

Close Date: 2024-12-31

Grant: Close

Dynamic regulatory network models of human response to influenza virus

Open Date: 2020-08-17

Close Date: 2025-05-31

Grant: Close

The LungMAP Data Coordination Center for Next Gen Systems Biology of Respiration

Open Date: 2019-08-23

Close Date: 2024-07-31

Grant: Close

Data Management and Coordinating Center: Rare Diseases Clinical Research Network

Open Date: 2019-08-05

Close Date: 2024-06-30

Articles (18)

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2021

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2021

Collaborators (3)

Jasbir Dhaliwal

Assistant Professor

Cincinnati Children's Hospital Medical Center

UNITED STATES

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Harinder Singh

Professor and Director

University of Pittsburgh

UNITED STATES

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H. Leighton Grimes

Professor

Cincinnati Children's Hospital Medical Center

UNITED STATES

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Surya Prasath

Research Interests

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About

Recent Grants

Articles (18)

Benchmarking HEp-2 cell segmentation methods in indirect immunofluorescence images - standard models to deep learning

Advancements in automated nuclei segmentation for histopathology using you only look once-driven approaches: A systematic review

Variational Weighted ℓp−ℓq$\ell _p-\ell _q$ Regularization for Hyperspectral Image Restoration Under Mixed Noise

Multimodal Ensemble Fusion Deep Learning Using Histopathological Images and Clinical Data for Glioma Subtype Classification

Artificial intelligence image-based prediction models in IBD exhibit high risk of bias: A systematic review

Deep learning-based IDH1 gene mutation prediction using histopathological imaging and clinical data

Hyperspectral image restoration using noise gradient and dual priors under mixed noise conditions

Color image restoration by filtering methods: a review

LRAP: Layered Ring Based Adaptive and Personalized Usability Model for Mobile Commerce Apps

Signal Approximations Based on Nonlinear and Optimal Piecewise Affine Functions

Decision level integration of unimodal and multimodal single cell data with scTriangulate

Data Augmentation Using Generative Adversarial Networks for Multi-Class Segmentation of Lung Confocal IF Images

Computational 2D and 3D Medical Image Data Compression Models

Recent developments in computational color image denoising with PDEs to deep learning: a review

Impulse denoising based on noise accumulation and harmonic analysis techniques

Brain tissue volume estimation to detect Alzheimer’s disease in magnetic resonance images

On a hybrid lossless compression technique for three‐dimensional medical images

POCASUM: policy categorizer and summarizer based on text mining and machine learning

Collaborators (3)

Jasbir Dhaliwal

Harinder Singh

H. Leighton Grimes

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