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Nathaniel Braman
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- affiliation: Case Western Reserve University, Department of Biomedical Engineering, Cleveland, OH, USA
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2020 – today
- 2022
- [p1]Ehsan Degan, Shafiq Abedin, David Beymer, Angshuman Deb, Nathaniel Braman, Benedikt Graf, Vandana V. Mukherjee:
Application of Federated Learning in Medical Imaging. Federated Learning 2022: 483-497 - [e1]Siva Teja Kakileti
, Maria Gabrani
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. Lecture Notes in Computer Science 13602, Springer 2022, ISBN 978-3-031-19659-1 [contents] - [i4]Nathaniel Braman, Prateek Prasanna, Kaustav Bera, Mehdi Alilou, Mohammadhadi Khorrami, Patrick Leo, Maryam Etesami, Manasa Vulchi, Paulette Turk, Amit Gupta
Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers. CoRR abs/2210.02273 (2022) - 2021
- [c8]Nathaniel Braman, Jacob W. H. Gordon, Emery T. Goossens, Caleb Willis, Martin C. Stumpe, Jagadish Venkataraman:
Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data. MICCAI (5) 2021: 667-677 - [i3]Nathaniel Braman, Jacob W. H. Gordon, Emery T. Goossens, Caleb Willis, Martin C. Stumpe, Jagadish Venkataraman:
Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data. CoRR abs/2107.00648 (2021) - 2020
- [c7]Amogh Hiremath, Rakesh Shiradkar, Nathaniel Braman, Prateek Prasanna
A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer. Medical Imaging: Computer-Aided Diagnosis 2020 - [c6]Sepideh Azarianpour
Computer extracted features related to the spatial arrangement of tumor-infiltrating lymphocytes predict overall survival in epithelial ovarian cancer receiving adjuvant chemotherapy. Medical Imaging: Digital Pathology 2020: 113200Q - [c5]Sara ArabYarmohammadi, Zelin Zhang, Patrick Leo, Marjan Firouznia, Andrew Janowczyk, Haojia Li, Nathaniel M. Braman, Kaustav Bera, Behtash G. Nezami, Howard Meyerson, Jun Xu, Leland Metheny, Anant Madabhushi:
Computationally derived cytological image markers for predicting risk of relapse in acute myeloid leukemia patients following bone marrow transplantation. Medical Imaging: Digital Pathology 2020: 1132004 - [i2]Nathaniel Braman
Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study. CoRR abs/2001.08570 (2020)
2010 – 2019
- 2019
- [c4]Prateek Prasanna
Morphology of vascular network in eyes with diabetic macular edema varies based on tolerance of aflibercept treatment interval length: preliminary findings. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 1095312 - [c3]Jeffrey E. Eben, Nathaniel Braman
Response Estimation Through Spatially Oriented Neural Network and Texture Ensemble (RESONATE). MICCAI (4) 2019: 602-610 - 2018
- [c2]Kavya Ravichandran, Nathaniel Braman
A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRI. Medical Imaging: Computer-Aided Diagnosis 2018: 105750C - [c1]Nathaniel Braman
Vascular Network Organization via Hough Transform (VaNgOGH): A Novel Radiomic Biomarker for Diagnosis and Treatment Response. MICCAI (2) 2018: 803-811 - [i1]Nathaniel Braman
Disease Detection in Weakly Annotated Volumetric Medical Images using a Convolutional LSTM Network. CoRR abs/1812.01087 (2018)
Coauthor Index
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