Search Results for author: Shawn Mathew

Found 6 papers, 5 papers with code

RT-GAN: Recurrent Temporal GAN for Adding Lightweight Temporal Consistency to Frame-Based Domain Translation Approaches

1 code implementation2 Oct 2023 Shawn Mathew, Saad Nadeem, Alvin C. Goh, Arie Kaufman

In this paper, we present a lightweight solution with a tunable temporal parameter, RT-GAN (Recurrent Temporal GAN), for adding temporal consistency to individual frame-based approaches that reduces training requirements by a factor of 5.

Video Generation

CLTS-GAN: Color-Lighting-Texture-Specular Reflection Augmentation for Colonoscopy

1 code implementation29 Jun 2022 Shawn Mathew, Saad Nadeem, Arie Kaufman

Automated analysis of optical colonoscopy (OC) video frames (to assist endoscopists during OC) is challenging due to variations in color, lighting, texture, and specular reflections.

NeuRegenerate: A Framework for Visualizing Neurodegeneration

no code implementations2 Feb 2022 Saeed Boorboor, Shawn Mathew, Mala Ananth, David Talmage, Lorna W. Role, Arie E. Kaufman

In this paper, we introduce NeuRegenerate, a novel end-to-end framework for the prediction and visualization of changes in neural fiber morphology within a subject, for specified age-timepoints. To predict projections, we present neuReGANerator, a deep-learning network based on cycle-consistent generative adversarial network (cycleGAN) that translates features of neuronal structures in a region, across age-timepoints, for large brain microscopy volumes.

Generative Adversarial Network Hallucination

FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos

1 code implementation23 Jun 2021 Shawn Mathew, Saad Nadeem, Arie Kaufman

Haustral folds are colon wall protrusions implicated for high polyp miss rate during optical colonoscopy procedures.

Generative Adversarial Network Translation

Visualizing Missing Surfaces In Colonoscopy Videos using Shared Latent Space Representations

1 code implementation18 Jan 2021 Shawn Mathew, Saad Nadeem, Arie Kaufman

This shared latent space captures the geometric information while deferring the color, texture, and specular information creation to additional Gaussian noise input.

Image-to-Image Translation Translation

Augmenting Colonoscopy using Extended and Directional CycleGAN for Lossy Image Translation

1 code implementation27 Mar 2020 Shawn Mathew, Saad Nadeem, Sruti Kumari, Arie Kaufman

In this paper, we present a deep learning framework, Extended and Directional CycleGAN, for lossy unpaired image-to-image translation between OC and VC to augment OC video sequences with scale-consistent depth information from VC, and augment VC with patient-specific textures, color and specular highlights from OC (e. g, for realistic polyp synthesis).

Image-to-Image Translation Translation

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