1 code implementation • 14 Sep 2023 • Dave Van Veen, Cara Van Uden, Louis Blankemeier, Jean-Benoit Delbrouck, Asad Aali, Christian Bluethgen, Anuj Pareek, Malgorzata Polacin, Eduardo Pontes Reis, Anna Seehofnerova, Nidhi Rohatgi, Poonam Hosamani, William Collins, Neera Ahuja, Curtis P. Langlotz, Jason Hom, Sergios Gatidis, John Pauly, Akshay S. Chaudhari
Analyzing vast textual data and summarizing key information from electronic health records imposes a substantial burden on how clinicians allocate their time.
1 code implementation • 2 May 2023 • Dave Van Veen, Cara Van Uden, Maayane Attias, Anuj Pareek, Christian Bluethgen, Malgorzata Polacin, Wah Chiu, Jean-Benoit Delbrouck, Juan Manuel Zambrano Chaves, Curtis P. Langlotz, Akshay S. Chaudhari, John Pauly
We systematically investigate lightweight strategies to adapt large language models (LLMs) for the task of radiology report summarization (RRS).
no code implementations • 17 Oct 2022 • Dave Van Veen, Rogier van der Sluijs, Batu Ozturkler, Arjun Desai, Christian Bluethgen, Robert D. Boutin, Marc H. Willis, Gordon Wetzstein, David Lindell, Shreyas Vasanawala, John Pauly, Akshay S. Chaudhari
We propose using a coordinate network decoder for the task of super-resolution in MRI.
no code implementations • 17 May 2022 • Arda Sahiner, Tolga Ergen, Batu Ozturkler, John Pauly, Morteza Mardani, Mert Pilanci
Vision transformers using self-attention or its proposed alternatives have demonstrated promising results in many image related tasks.
1 code implementation • 21 Apr 2022 • Beliz Gunel, Arda Sahiner, Arjun D. Desai, Akshay S. Chaudhari, Shreyas Vasanawala, Mert Pilanci, John Pauly
Unrolled neural networks have enabled state-of-the-art reconstruction performance and fast inference times for the accelerated magnetic resonance imaging (MRI) reconstruction task.
1 code implementation • NeurIPS Workshop Deep_Invers 2021 • Liyue Shen, John Pauly, Lei Xing
The method differs fundamentally from previous deep learning-based image reconstruction approaches in that NeRP exploits the internal information in an image prior, and the physics of the sparsely sampled measurements to produce a representation of the unknown subject.
1 code implementation • ICLR 2022 • Arda Sahiner, Tolga Ergen, Batu Ozturkler, Burak Bartan, John Pauly, Morteza Mardani, Mert Pilanci
In this work, we analyze the training of Wasserstein GANs with two-layer neural network discriminators through the lens of convex duality, and for a variety of generators expose the conditions under which Wasserstein GANs can be solved exactly with convex optimization approaches, or can be represented as convex-concave games.
no code implementations • 25 May 2021 • Liyue Shen, Wei Zhao, Dante Capaldi, John Pauly, Lei Xing
Deep learning affords enormous opportunities to augment the armamentarium of biomedical imaging, albeit its design and implementation have potential flaws.
no code implementations • 8 Mar 2021 • Ke Wang, Enhao Gong, Yuxin Zhang, Suchadrima Banerjee, Greg Zaharchuk, John Pauly
Multi-contrast Magnetic Resonance Imaging (MRI) acquisitions from a single scan have tremendous potential to streamline exams and reduce imaging time.
no code implementations • ICLR 2022 • Tolga Ergen, Arda Sahiner, Batu Ozturkler, John Pauly, Morteza Mardani, Mert Pilanci
Batch Normalization (BN) is a commonly used technique to accelerate and stabilize training of deep neural networks.
no code implementations • ICLR 2021 • Arda Sahiner, Tolga Ergen, John Pauly, Mert Pilanci
We describe the convex semi-infinite dual of the two-layer vector-output ReLU neural network training problem.
no code implementations • ICLR 2021 • Arda Sahiner, Morteza Mardani, Batu Ozturkler, Mert Pilanci, John Pauly
Neural networks have shown tremendous potential for reconstructing high-resolution images in inverse problems.
no code implementations • 10 Jun 2019 • Morteza Mardani, Qingyun Sun, Vardan Papyan, Shreyas Vasanawala, John Pauly, David Donoho
Leveraging the Stein's Unbiased Risk Estimator (SURE), this paper analyzes the generalization risk with its bias and variance components for recurrent unrolled networks.
no code implementations • 31 Jan 2019 • Vineet Edupuganti, Morteza Mardani, Shreyas Vasanawala, John Pauly
Reliable MRI is crucial for accurate interpretation in therapeutic and diagnostic tasks.
1 code implementation • NeurIPS 2018 • Morteza Mardani, Qingyun Sun, Shreyas Vasawanala, Vardan Papyan, Hatef Monajemi, John Pauly, David Donoho
Recovering high-resolution images from limited sensory data typically leads to a serious ill-posed inverse problem, demanding inversion algorithms that effectively capture the prior information.
1 code implementation • 15 Mar 2018 • Jaeyeon Yoon, Enhao Gong, Itthi Chatnuntawech, Berkin Bilgic, Jingu Lee, Woojin Jung, Jingyu Ko, Hosan Jung, Kawin Setsompop, Greg Zaharchuk, Eung Yeop Kim, John Pauly, Jong-Ho Lee
The QSMnet maps of the test dataset were compared with those from TKD and MEDI for image quality and consistency in multiple head orientations.
Image and Video Processing
no code implementations • 12 Dec 2017 • Junshen Xu, Enhao Gong, John Pauly, Greg Zaharchuk
Experiments shows the proposed method can reconstruct low-dose PET image to a standard-dose quality with only two-hundredth dose.
no code implementations • 27 Nov 2017 • Morteza Mardani, Hatef Monajemi, Vardan Papyan, Shreyas Vasanawala, David Donoho, John Pauly
Building effective priors is however challenged by the low train and test overhead dictated by real-time tasks; and the need for retrieving visually "plausible" and physically "feasible" images with minimal hallucination.