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Darvin Yi
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2020 – today
- 2024
- [c7]Isabella Poles, Eleonora D'Arnese, Luca G. Cellamare, Marco D. Santambrogio, Darvin Yi:
Repurposing the Image Generative Potential: Exploiting GANs to Grade Diabetic Retinopathy. CVPR Workshops 2024: 2305-2314 - [c6]Isabella Poles, Eleonora D'Arnese, Darvin Yi, Marco D. Santambrogio:
A Physiological Variability Inspired Spatial Regularization for Joint Rigid-Deformable Abdominal MR Image Registration. ISBI 2024: 1-5 - [i17]George R. Nahass, Ghasem Yazdanpanah, Madison Cheung, Alex Palacios, Jeffery Peterson, Kevin Heinze, Sasha Hubschman, Chad A. Purnell, Pete Setabutr, Ann Q. Tran, Darvin Yi:
State-of-the-Art Periorbital Distance Prediction and Disease Classification Using Periorbital Features. CoRR abs/2409.18769 (2024) - [i16]George R. Nahass, Emma Koehler, Nicholas Tomaras, Danny Lopez, Madison Cheung, Alexander Palacios, Jeffery Peterson, Sacha Hubschman, Kelsey Green, Chad A. Purnell, Pete Setabutr, Ann Q. Tran, Darvin Yi:
Open-Source Periorbital Segmentation Dataset for Ophthalmic Applications. CoRR abs/2409.20407 (2024) - 2022
- [j3]Jon André Ottesen, Darvin Yi, Elizabeth Tong, Michael Iv
, Anna Latysheva, Cathrine Saxhaug, Kari Dolven Jacobsen, Åslaug Helland, Kyrre Eeg Emblem, Daniel L. Rubin, Atle Bjørnerud, Greg Zaharchuk, Endre Grøvik:
2.5D and 3D segmentation of brain metastases with deep learning on multinational MRI data. Frontiers Neuroinformatics 16 (2022) - 2021
- [j2]Endre Grøvik, Darvin Yi, Michael Iv
Handling missing MRI sequences in deep learning segmentation of brain metastases: a multicenter study. npj Digit. Medicine 4 (2021) - [c5]Nooshin Mojab, Vahid Noroozi, Abdullah Aleem, Manoj Prabhakar Nallabothula, Joseph Baker, Dimitri T. Azar, Mark Rosenblatt, R. V. Paul Chan, Darvin Yi, Philip S. Yu, Joelle A. Hallak:
I-ODA, Real-world Multi-modal Longitudinal Data for Ophthalmic Applications. HEALTHINF 2021: 566-574 - [c4]Nooshin Mojab, Philip S. Yu, Joelle A. Hallak, Darvin Yi:
CvS: Classification via Segmentation For Small Datasets. BMVC 2021: 174 - [i15]Nooshin Mojab, Vahid Noroozi, Abdullah Aleem, Manoj Prabhakar Nallabothula, Joseph Baker, Dimitri T. Azar, Mark Rosenblatt, R. V. Paul Chan, Darvin Yi, Philip S. Yu, Joelle A. Hallak:
I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications. CoRR abs/2104.02609 (2021) - [i14]Abdullah Aleem, Manoj Prabhakar Nallabothula, Pete Setabutr, Joelle A. Hallak, Darvin Yi:
AutoPtosis. CoRR abs/2106.03905 (2021) - [i13]Nooshin Mojab, Philip S. Yu, Joelle A. Hallak, Darvin Yi:
CvS: Classification via Segmentation For Small Datasets. CoRR abs/2111.00042 (2021) - 2020
- [c3]Nooshin Mojab, Vahid Noroozi, Darvin Yi, Manoj Prabhakar Nallabothula, Abdullah Aleem, Philip S. Yu, Joelle A. Hallak:
Real-World Multi-Domain Data Applications for Generalizations to Clinical Settings. ICMLA 2020: 677-684 - [c2]Darvin Yi, Endre Grøvik, Michael Iv, Elizabeth Tong, Greg Zaharchuk, Daniel L. Rubin:
Brain Metastasis Segmentation Network Trained with Robustness to Annotations with Multiple False Negatives. MIDL 2020: 867-880 - [i12]Darvin Yi, Endre Grøvik
Brain Metastasis Segmentation Network Trained with Robustness to Annotations with Multiple False Negatives. CoRR abs/2001.09501 (2020) - [i11]Darvin Yi, Endre Grøvik, Michael Iv, Elizabeth Tong, Greg Zaharchuk, Daniel L. Rubin:
Random Bundle: Brain Metastases Segmentation Ensembling through Annotation Randomization. CoRR abs/2002.09809 (2020) - [i10]Nooshin Mojab, Vahid Noroozi, Darvin Yi, Manoj Prabhakar Nallabothula, Abdullah Aleem, Philip S. Yu, Joelle A. Hallak:
Real-World Multi-Domain Data Applications for Generalizations to Clinical Settings. CoRR abs/2007.12672 (2020)
2010 – 2019
- 2019
- [i9]Endre Grøvik, Darvin Yi, Michael Iv, Elisabeth Tong, Daniel L. Rubin, Greg Zaharchuk:
Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI. CoRR abs/1903.07988 (2019) - [i8]Ameya Phalak, Zhao Chen, Darvin Yi, Khushi Gupta, Vijay Badrinarayanan, Andrew Rabinovich:
DeepPerimeter: Indoor Boundary Estimation from Posed Monocular Sequences. CoRR abs/1904.11595 (2019) - [i7]Darvin Yi, Endre Grøvik
MRI Pulse Sequence Integration for Deep-Learning Based Brain Metastasis Segmentation. CoRR abs/1912.08775 (2019) - [i6]Endre Grøvik
Handling Missing MRI Input Data in Deep Learning Segmentation of Brain Metastases: A Multi-Center Study. CoRR abs/1912.11966 (2019) - 2018
- [j1]Ken Chang, Niranjan Balachandar
Distributed deep learning networks among institutions for medical imaging. J. Am. Medical Informatics Assoc. 25(8): 945-954 (2018) - [i5]Blaine Rister, Darvin Yi, Kaushik Shivakumar, Tomomi Nobashi, Daniel L. Rubin:
CT organ segmentation using GPU data augmentation, unsupervised labels and IOU loss. CoRR abs/1811.11226 (2018) - 2017
- [c1]Zeshan Hussain, Francisco Gimenez, Darvin Yi, Daniel L. Rubin:
Differential Data Augmentation Techniques for Medical Imaging Classification Tasks. AMIA 2017 - [i4]Zhao Chen, Darvin Yi:
The Game Imitation: Deep Supervised Convolutional Networks for Quick Video Game AI. CoRR abs/1702.05663 (2017) - [i3]Darvin Yi, Rebecca Lynn Sawyer, David Cohn III, Jared Dunnmon, Carson K. Lam, Xuerong Xiao, Daniel L. Rubin:
Optimizing and Visualizing Deep Learning for Benign/Malignant Classification in Breast Tumors. CoRR abs/1705.06362 (2017) - [i2]Ken Chang, Niranjan Balachandar
Institutionally Distributed Deep Learning Networks. CoRR abs/1709.05929 (2017) - 2016
- [i1]Darvin Yi, Mu Zhou, Zhao Chen, Olivier Gevaert:
3-D Convolutional Neural Networks for Glioblastoma Segmentation. CoRR abs/1611.04534 (2016)
Coauthor Index
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