no code implementations • 15 Apr 2024 • Ammar Ahmed Pallikonda Latheef, Alberto Santamaria-Pang, Craig K Jones, Haris I Sair
Brain networks display a hierarchical organization, a complexity that poses a challenge for existing deep learning models, often structured as flat classifiers, leading to difficulties in interpretability and the 'black box' issue.
no code implementations • 15 Jan 2024 • Ho Hin Lee, Yu Gu, Theodore Zhao, Yanbo Xu, Jianwei Yang, Naoto Usuyama, Cliff Wong, Mu Wei, Bennett A. Landman, Yuankai Huo, Alberto Santamaria-Pang, Hoifung Poon
This transformative technology, originally developed for general-purpose computer vision, has found rapid application in medical image processing.
1 code implementation • 23 Nov 2023 • Asma Ben Abacha, Alberto Santamaria-Pang, Ho Hin Lee, Jameson Merkow, Qin Cai, Surya Teja Devarakonda, Abdullah Islam, Julia Gong, Matthew P. Lungren, Thomas Lin, Noel C Codella, Ivan Tarapov
The increasing use of medical imaging in healthcare settings presents a significant challenge due to the increasing workload for radiologists, yet it also offers opportunity for enhancing healthcare outcomes if effectively leveraged.
no code implementations • 9 May 2023 • Ho Hin Lee, Alberto Santamaria-Pang, Jameson Merkow, Ozan Oktay, Fernando Pérez-García, Javier Alvarez-Valle, Ivan Tarapov
We introduce a novel Region-based contrastive pretraining for Medical Image Retrieval (RegionMIR) that demonstrates the feasibility of medical image retrieval with similar anatomical regions.
no code implementations • 5 May 2023 • Ammar Ahmed Pallikonda Latheef, Sejal Ghate, Zhipeng Hui, Alberto Santamaria-Pang, Ivan Tarapov, Haris I Sair, Craig K Jones
We prove the generalizability of our method by showing that the MLP performs at 100% accuracy in the holdout dataset and 98. 3% accuracy in three other sites' fMRI acquisitions.
no code implementations • 16 Sep 2022 • Sejal Ghate, Alberto Santamaria-Pang, Ivan Tarapov, Haris I Sair, Craig K Jones
We propose an end-to-end reproducible pipeline which incorporates image processing of rs-fMRI in a cloud-based workflow while using deep learning to automate the classification of RSNs.
no code implementations • 26 Jul 2021 • Alberto Santamaria-Pang, Jianwei Qiu, Aritra Chowdhury, James Kubricht, Peter Tu, Iyer Naresh, Nurali Virani
Third, we generate new adversarial images by projecting back the original coefficients from the low scale and the perturbed coefficients from the high scale sub-space.
1 code implementation • 22 Aug 2020 • Aritra Chowdhury, Alberto Santamaria-Pang, James R. Kubricht, Peter Tu
In this work, we demonstrate for the first time, the emer-gence of deep symbolic representations of emergent language in the frame-work of image classification.
no code implementations • 22 Aug 2020 • Aritra Chowdhury, Alberto Santamaria-Pang, James R. Kubricht, Jianwei Qiu, Peter Tu
We show state of the art results for segmentation of COVID-19 lung infections in CT.
no code implementations • 18 Jul 2020 • Alberto Santamaria-Pang, Anup Sood, Dan Meyer, Aritra Chowdhury, Fiona Ginty
We present a method for automatic cell classification in tissue samples using an automated training set from multiplexed immunofluorescence images.
no code implementations • 18 Jul 2020 • Alberto Santamaria-Pang, James Kubricht, Aritra Chowdhury, Chitresh Bhushan, Peter Tu
A UNet-like architecture is used to generate input to the Sender network which produces a symbolic sentence, and a Receiver network co-generates the segmentation mask based on the sentence.
no code implementations • 18 Jul 2020 • Aritra Chowdhury, James R. Kubricht, Anup Sood, Peter Tu, Alberto Santamaria-Pang
In one form of the game, a sender and a receiver observe a set of cells from 5 different cell phenotypes.