Nathaniel Braman

13 papers Journal 4Unranked 7
YearRankTypeTitle / Venue / Authors
2022 — ch.
Application of Federated Learning in Medical Imaging.
Federated Learning
Ehsan Degan, Shafiq Abedin, David Beymer, Angshuman Deb, Nathaniel Braman, Benedikt Graf, Vandana V. Mukherjee
2022 — ed.
Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery - First MICCAI Workshop, AIIIMA 2022, and First MICCAI Workshop, MIABID 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18 and 22, 2022, Proceedings
AIIIMA/MIABID@MICCAI
Siva Teja Kakileti, Maria Gabrani, Geetha Manjunath, Michal Rosen-Zvi, Nathaniel Braman, Robert G. Schwartz, Alejandro F. Frangi, Pau-Choo Chung, Christopher J. Weight, Vekataraman Jagadish
2022 J jnl
Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers.
CoRR
Nathaniel Braman, Prateek Prasanna, Kaustav Bera, Mehdi Alilou, Mohammadhadi Khorrami, Patrick Leo, Maryam Etesami, Manasa Vulchi, Paulette Turk, Amit Gupta, Prantesh Jain, Pingfu Fu, Nathan Pennell, Vamsidhar Velcheti, Jame Abraham, Donna Plecha, Anant Madabhushi
2021 — conf
Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data.
MICCAI (5)
Nathaniel Braman, Jacob W. H. Gordon, Emery T. Goossens, Caleb Willis, Martin C. Stumpe, Jagadish Venkataraman
2021 J jnl
Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data.
CoRR
Nathaniel Braman, Jacob W. H. Gordon, Emery T. Goossens, Caleb Willis, Martin C. Stumpe, Jagadish Venkataraman
2020 — conf
A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer.
Computer-Aided Diagnosis
Amogh Hiremath, Rakesh Shiradkar, Nathaniel Braman, Prateek Prasanna, Ardeshir R. Rastinehad, Andrei S. Purysko, Anant Madabhushi
2020 — conf
Computer extracted features related to the spatial arrangement of tumor-infiltrating lymphocytes predict overall survival in epithelial ovarian cancer receiving adjuvant chemotherapy.
Digital Pathology
Sepideh Azarianpour, Germán Corredor, Kaustav Bera, Patrick Leo, Nathaniel Braman, Pingfu Fu, Haider Mahdi, Anant Madabhushi
2020 J jnl
Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study.
CoRR
Nathaniel Braman, Mohammed El Adoui, Manasa Vulchi, Paulette Turk, Maryam Etesami, Pingfu Fu, Kaustav Bera, Stylianos Drisis, Vinay Varadan, Donna Plecha, Mohammed Benjelloun, Jame Abraham, Anant Madabhushi
2019 — conf
Morphology of vascular network in eyes with diabetic macular edema varies based on tolerance of aflibercept treatment interval length: preliminary findings.
Biomedical Applications in Molecular, Structural, and Functional Imaging
Prateek Prasanna, Justis Ehlers, Nathaniel Braman, Natalia Figueredo, Vishal Bobba, Sumit Sharma, Sunil Srivastava, Anant Madabhushi
2019 — conf
Response Estimation Through Spatially Oriented Neural Network and Texture Ensemble (RESONATE).
MICCAI (4)
Jeffrey E. Eben, Nathaniel Braman, Anant Madabhushi
2018 — conf
A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRI.
Computer-Aided Diagnosis
Kavya Ravichandran, Nathaniel Braman, Andrew Janowczyk, Anant Madabhushi
2018 J jnl
Disease Detection in Weakly Annotated Volumetric Medical Images using a Convolutional LSTM Network.
CoRR
Nathaniel Braman, David Beymer, Ehsan Dehghan
2018 — conf
Vascular Network Organization via Hough Transform (VaNgOGH): A Novel Radiomic Biomarker for Diagnosis and Treatment Response.
MICCAI (2)
Nathaniel Braman, Prateek Prasanna, Mehdi Alilou, Niha G. Beig, Anant Madabhushi