1 code implementation • ACL 2022 • Jean-Benoit Delbrouck, Khaled Saab, Maya Varma, Sabri Eyuboglu, Pierre Chambon, Jared Dunnmon, Juan Zambrano, Akshay Chaudhari, Curtis Langlotz
There is a growing need to model interactions between data modalities (e. g., vision, language) — both to improve AI predictions on existing tasks and to enable new applications.
1 code implementation • 11 Feb 2025 • Joseph Paul Cohen, Louis Blankemeier, Akshay Chaudhari
Counterfactual explanations in medical imaging are critical for understanding the predictions made by deep learning models.
no code implementations • 20 Jan 2025 • Ivan Lopez, Fateme Nateghi Haredasht, Kaitlin Caoili, Jonathan H Chen, Akshay Chaudhari
We propose an embedding-driven approach that uses diversity sampling from a small set of real clinical notes to guide large language models in few-shot prompting, generating synthetic text that better reflects clinical syntax.
no code implementations • 2 Dec 2024 • Christian Bluethgen, Dave Van Veen, Cyril Zakka, Katherine Link, Aaron Fanous, Roxana Daneshjou, Thomas Frauenfelder, Curtis Langlotz, Sergios Gatidis, Akshay Chaudhari
At the heart of radiological practice is the challenge of integrating complex imaging data with clinical information to produce actionable insights.
no code implementations • 27 Nov 2024 • Magdalini Paschali, Zhihong Chen, Louis Blankemeier, Maya Varma, Alaa Youssef, Christian Bluethgen, Curtis Langlotz, Sergios Gatidis, Akshay Chaudhari
Given the potentially transformative impact that foundation models can have on the field of radiology, this review aims to establish a standardized terminology concerning foundation models, with a specific focus on the requirements of training data, model training paradigms, model capabilities, and evaluation strategies.
no code implementations • 27 Nov 2024 • Eva Prakash, Jeya Maria Jose Valanarasu, Zhihong Chen, Eduardo Pontes Reis, Andrew Johnston, Anuj Pareek, Christian Bluethgen, Sergios Gatidis, Cameron Olsen, Akshay Chaudhari, Andrew Ng, Curtis Langlotz
We explored methods like using a proxy model and using radiologist feedback to improve the quality of synthetic data.
1 code implementation • 6 Nov 2024 • Maya Varma, Jean-Benoit Delbrouck, Zhihong Chen, Akshay Chaudhari, Curtis Langlotz
Fine-tuned vision-language models (VLMs) often capture spurious correlations between image features and textual attributes, resulting in degraded zero-shot performance at test time.
1 code implementation • 15 Oct 2024 • Shizhe He, Magdalini Paschali, Jiahong Ouyang, Adnan Masood, Akshay Chaudhari, Ehsan Adeli
This approach requires moving beyond traditional representation learning methods, as we need a representation vector space that allows for the application of the same SO(3) operation in that space.
no code implementations • 1 Oct 2024 • Magdalini Paschali, Yu Hang Jiang, Spencer Siegel, Camila Gonzalez, Kilian M. Pohl, Akshay Chaudhari, Qingyu Zhao
To this end, we propose to model the subject weights as a linear combination of the eigenbases of a spectral population graph that captures the similarity of factors across subjects.
1 code implementation • 14 Jun 2024 • Sophie Ostmeier, Brian Axelrod, Michael E. Moseley, Akshay Chaudhari, Curtis Langlotz
While Rotary Position Embeddings (RoPE) for large language models have become widely adopted, their application for other modalities has been slower.
no code implementations • 14 Jun 2024 • Yoni Gozlan, Antoine Falisse, Scott Uhlrich, Anthony Gatti, Michael Black, Akshay Chaudhari
To mitigate this challenge, we introduce SynthPose, a new approach that enables finetuning of pre-trained 2D human pose models to predict an arbitrarily denser set of keypoints for accurate kinematic analysis through the use of synthetic data.
no code implementations • 16 May 2024 • Joseph Cho, Cyril Zakka, Dhamanpreet Kaur, Rohan Shad, Ross Wightman, Akshay Chaudhari, William Hiesinger
Diffusion models have recently gained significant traction due to their ability to generate high-fidelity and diverse images and videos conditioned on text prompts.
no code implementations • 30 Apr 2024 • Cyril Zakka, Joseph Cho, Gracia Fahed, Rohan Shad, Michael Moor, Robyn Fong, Dhamanpreet Kaur, Vishnu Ravi, Oliver Aalami, Roxana Daneshjou, Akshay Chaudhari, William Hiesinger
Clinicians spend large amounts of time on clinical documentation, and inefficiencies impact quality of care and increase clinician burnout.
no code implementations • 24 Apr 2024 • Reinhard Heckel, Mathews Jacob, Akshay Chaudhari, Or Perlman, Efrat Shimron
Deep learning (DL) has recently emerged as a pivotal technology for enhancing magnetic resonance imaging (MRI), a critical tool in diagnostic radiology.
no code implementations • 12 Mar 2024 • Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu, Hanwen Xu, Naoto Usuyama, Sheng Zhang, Fei Wang, Yujia Xie, Mahmoud Khademi, ZiYi Yang, Hany Awadalla, Julia Gong, Houdong Hu, Jianwei Yang, Chunyuan Li, Jianfeng Gao, Yu Gu, Cliff Wong, Mu Wei, Tristan Naumann, Muhao Chen, Matthew P. Lungren, Akshay Chaudhari, Serena Yeung-Levy, Curtis P. Langlotz, Sheng Wang, Hoifung Poon
Frontier general-domain models such as GPT-4V still have significant performance gaps in multimodal biomedical applications.
1 code implementation • 1 Dec 2023 • Joseph Paul Cohen, Louis Blankemeier, Akshay Chaudhari
We propose the counterfactual (CF) alignment method to detect and quantify spurious correlations of black box classifiers.
1 code implementation • ICCV 2023 • Maya Varma, Jean-Benoit Delbrouck, Sarah Hooper, Akshay Chaudhari, Curtis Langlotz
The first key contribution of this work is to demonstrate through systematic evaluations that as the pairwise complexity of the training dataset increases, standard VLMs struggle to learn region-attribute relationships, exhibiting performance degradations of up to 37% on retrieval tasks.
1 code implementation • 2 Apr 2023 • Joseph Paul Cohen, Rupert Brooks, Sovann En, Evan Zucker, Anuj Pareek, Matthew Lungren, Akshay Chaudhari
This study evaluates the effect of counterfactual explanations on the interpretation of chest X-rays.
3 code implementations • 6 Feb 2023 • Tiange Xiang, Mahmut Yurt, Ali B Syed, Kawin Setsompop, Akshay Chaudhari
Magnetic resonance imaging (MRI) is a common and life-saving medical imaging technique.
1 code implementation • 30 Jan 2023 • Rogier van der Sluijs, Nandita Bhaskhar, Daniel Rubin, Curtis Langlotz, Akshay Chaudhari
Thus, it is unknown whether common augmentation strategies employed in Siamese representation learning generalize to medical images and to what extent.
1 code implementation • 23 Nov 2022 • Pierre Chambon, Christian Bluethgen, Jean-Benoit Delbrouck, Rogier van der Sluijs, Małgorzata Połacin, Juan Manuel Zambrano Chaves, Tanishq Mathew Abraham, Shivanshu Purohit, Curtis P. Langlotz, Akshay Chaudhari
We present evidence that the resulting model (RoentGen) is able to create visually convincing, diverse synthetic CXR images, and that the output can be controlled to a new extent by using free-form text prompts including radiology-specific language.
no code implementations • 9 Oct 2022 • Pierre Chambon, Christian Bluethgen, Curtis P. Langlotz, Akshay Chaudhari
Multi-modal foundation models are typically trained on millions of pairs of natural images and text captions, frequently obtained through web-crawling approaches.
1 code implementation • 31 Oct 2021 • Joseph Paul Cohen, Joseph D. Viviano, Paul Bertin, Paul Morrison, Parsa Torabian, Matteo Guarrera, Matthew P Lungren, Akshay Chaudhari, Rupert Brooks, Mohammad Hashir, Hadrien Bertrand
TorchXRayVision is an open source software library for working with chest X-ray datasets and deep learning models.
no code implementations • NeurIPS Workshop Deep_Invers 2021 • Philip M Adamson, Beliz Gunel, Jeffrey Dominic, Arjun D Desai, Daniel Spielman, Shreyas Vasanawala, John M. Pauly, Akshay Chaudhari
Self-supervised learning (SSL) has become a popular pre-training tool due to its ability to capture generalizable and domain-specific feature representations of the underlying data for downstream tasks.
1 code implementation • 29 Sep 2021 • Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Srini Bala, Daniel J. Beutel, Victor Bittorf, Akshay Chaudhari, Alexander Chowdhury, Cody Coleman, Bala Desinghu, Gregory Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Junyi Guo, Xinyuan Huang, David Kanter, Satyananda Kashyap, Nicholas Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G Anthony Reina, Pablo Ribalta, Jacob Rosenthal, Abhishek Singh, Jayaraman J. Thiagarajan, Anna Wuest, Maria Xenochristou, Daguang Xu, Poonam Yadav, Michael Rosenthal, Massimo Loda, Jason M. Johnson, Peter Mattson
Medical AI has tremendous potential to advance healthcare by supporting the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving provider and patient experience.
no code implementations • NeurIPS 2021 • Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias
Explanation techniques that synthesize small, interpretable changes to a given image while producing desired changes in the model prediction have become popular for introspecting black-box models.
no code implementations • 3 Aug 2021 • Anirudh Joshi, Sabri Eyuboglu, Shih-Cheng Huang, Jared Dunnmon, Arjun Soin, Guido Davidzon, Akshay Chaudhari, Matthew P Lungren
FDG PET/CT imaging is a resource intensive examination critical for managing malignant disease and is particularly important for longitudinal assessment during therapy.
3 code implementations • 18 Feb 2021 • Joseph Paul Cohen, Rupert Brooks, Sovann En, Evan Zucker, Anuj Pareek, Matthew P. Lungren, Akshay Chaudhari
We also found that the Latent Shift explanation allows a user to have more confidence in true positive predictions compared to traditional approaches (0. 15$\pm$0. 95 in a 5 point scale with p=0. 01) with only a small increase in false positive predictions (0. 04$\pm$1. 06 with p=0. 57).
no code implementations • 1 Feb 2021 • Simone Angela Winkler, Isabelle Saniour, Akshay Chaudhari, Fraser Robb, J Thomas Vaughan
We trained the software with a small database of image as a feasibility study and achieved successful proof of concept for both field strengths.
1 code implementation • 22 Dec 2020 • Kevin A. Thomas, Dominik Krzemiński, Łukasz Kidziński, Rohan Paul, Elka B. Rubin, Eni Halilaj, Marianne S. Black, Akshay Chaudhari, Garry E. Gold, Scott L. Delp
Subregional T2 values and four-year changes were calculated using a musculoskeletal radiologist's segmentations (Reader 1) and the model's segmentations.
no code implementations • 7 Aug 2018 • Akshay Chaudhari, Zhongnan Fang, Jin Hyung Lee, Garry Gold, Brian Hargreaves
Obtaining magnetic resonance images (MRI) with high resolution and generating quantitative image-based biomarkers for assessing tissue biochemistry is crucial in clinical and research applications.