Sung Min Ha

According to our database, Sung Min Ha authored at least 8 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Scalable NMF via linearly optimized data compression.

Sung Min Ha, Abdalla Bani, Aristeidis Sotiras

Proceedings of the Medical Imaging 2023: Image Processing, 2023

Morphological Versus Functional Network Organization: A Comparison Between Structural Covariance Networks and Probabilistic Functional Modes.

Petra Lenzini, Thomas Earnest, Sung Min Ha, Abdalla Bani, Aristeidis Sotiras, Janine Bijsterbosch

Proceedings of the Machine Learning in Clinical Neuroimaging - 6th International Workshop, 2023

Scalable Orthonormal Projective NMF via Diversified Stochastic Optimization.

Abdalla Bani, Sung Min Ha, Pan Xiao, Thomas Earnest, John Lee, Aristeidis Sotiras

Proceedings of the Information Processing in Medical Imaging, 2023

2020

Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training.

Siddhesh P. Thakur, Jimit Doshi, Sarthak Pati, Saima Rathore, Chiharu Sako, Michel Bilello, Sung Min Ha, Gaurav Shukla, Adam E. Flanders, Aikaterini Kotrotsou, Mikhail Milchenko, Spencer Liem, Gregory S. Alexander, Joseph Lombardo, Joshua D. Palmer, Pamela LaMontagne, Arash Nazeri, Sanjay N. Talbar, Spyridon Bakas

NeuroImage, 2020

Integrative radiomic analysis for pre-surgical prognostic stratification of glioblastoma patients: from advanced to basic MRI protocols.

Spyridon Bakas, Gaurav Shukla, Hamed Akbari, Güray Erus, Aristeidis Sotiras, Saima Rathore, Chiharu Sako, Sung Min Ha, Martin Rozycki, Ashish Singh, Russell T. Shinohara, Michel Bilello, Christos Davatzikos

Proceedings of the Medical Imaging 2020: Image-Guided Procedures, 2020

2019

Skull-Stripping of Glioblastoma MRI Scans Using 3D Deep Learning.

Siddhesh P. Thakur, Jimit Doshi, Sarthak Pati, Sung Min Ha, Chiharu Sako, Sanjay N. Talbar, Uday Kulkarni, Christos Davatzikos, Güray Erus, Spyridon Bakas

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview.

Sarthak Pati, Ashish Singh, Saima Rathore, Aimilia Gastounioti, Mark Bergman, Phuc Ngo, Sung Min Ha, Dimitrios Bounias, James Minock, Grayson Murphy, Hongming Li, Amit Bhattarai, Adam Wolf, Patmaa Sridaran, Ratheesh Kalarot, Hamed Akbari, Aristeidis Sotiras, Siddhesh P. Thakur, Ragini Verma, Russell T. Shinohara, Paul A. Yushkevich, Yong Fan, Despina Kontos, Christos Davatzikos, Spyridon Bakas

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.

Spyridon Bakas, Mauricio Reyes, András Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipková, John B. Freymann, Justin S. Kirby, Michel Bilello, Hassan M. Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka R. Colen, Aikaterini Kotrotsou, Pamela LaMontagne, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Marc-André Weber, Abhishek Mahajan, Ujjwal Baid, Dongjin Kwon, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Alex Varghese, Tran Anh Tuan, Tal Arbel, Aaron Avery, Pranjal B., Subhashis Banerjee, Thomas Batchelder, Kayhan N. Batmanghelich, Enzo Battistella, Martin Bendszus, Eze Benson, José Bernal, George Biros, Mariano Cabezas, Siddhartha Chandra, Yi-Ju Chang, et al.

CoRR, 2018