533 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Cornell UniversityUS77 papers
- Harvard UniversityUS11 papers
- Stanford UniversityUS9 papers
- CitigroupUS7 papers
- Columbia UniversityUS7 papers
- Massachusetts Institute of TechnologyUS7 papers
- Memorial Sloan Kettering Cancer CenterUS7 papers
- The University of Texas at AustinUS7 papers
- University of PennsylvaniaUS7 papers
- Georgia Institute of TechnologyUS6 papers
- Icahn School of Medicine at Mount SinaiUS6 papers
- Mayo ClinicUS6 papers
8 papers · 1 filter
Automatic Tuning of Denoising Algorithms Parameters Without Ground Truth
Arthur Floquet, Sayantan Dutta, Emmanuel Soubies +2
Denoising is omnipresent in image processing. It is usually addressed with algorithms relying on a set of hyperparameters that control the quality of the recovered image. Manual tu…
mcLARO: Multi-Contrast Learned Acquisition and Reconstruction Optimization for simultaneous quantitative multi-parametric mapping
Jinwei Zhang, Thanh D. Nguyen, Eddy Solomon +6
Purpose: To develop a method for rapid sub-millimeter T1, T2, T2* and QSM mapping in a single scan using multi-contrast Learned Acquisition and Reconstruction Optimization (mcLARO)…
Maximum Spherical Mean Value (mSMV) Filtering for Whole Brain Quantitative Susceptibility Mapping
Alexandra G. Roberts, Dominick J. Romano, Mert Şişman +6
To develop a tissue field filtering algorithm, called maximum Spherical Mean Value (mSMV), for reducing shadow artifacts in quantitative susceptibility mapping (QSM) of the brain w…
DIVA: Deep Unfolded Network from Quantum Interactive Patches for Image Restoration
Sayantan Dutta, Adrian Basarab, Bertrand Georgeot +1
This paper presents a deep neural network called DIVA unfolding a baseline adaptive denoising algorithm (De-QuIP), relying on the theory of quantum many-body physics. Furthermore,…
COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature
Yifan Peng, Yu-Xing Tang, Sungwon Lee +3
The latest threat to global health is the COVID-19 outbreak. Although there exist large datasets of chest X-rays (CXR) and computed tomography (CT) scans, few COVID-19 image collec…
Advance Warning Methodologies for COVID-19 using Chest X-Ray Images
Mete Ahishali, Aysen Degerli, Mehmet Yamac +6
Coronavirus disease 2019 (COVID-19) has rapidly become a global health concern after its first known detection in December 2019. As a result, accurate and reliable advance warning…
RSANet: Recurrent Slice-wise Attention Network for Multiple Sclerosis Lesion Segmentation
Hang Zhang, Jinwei Zhang, Qihao Zhang +7
Brain lesion volume measured on T2 weighted MRI images is a clinically important disease marker in multiple sclerosis (MS). Manual delineation of MS lesions is a time-consuming and…
Deep Multi-Magnification Networks for Multi-Class Breast Cancer Image Segmentation
David Joon Ho, Dig V. K. Yarlagadda, Timothy M. D'Alfonso +6
Pathologic analysis of surgical excision specimens for breast carcinoma is important to evaluate the completeness of surgical excision and has implications for future treatment. Th…