Automated drusen segmentation and quantification in SD-OCT images. - Qiang Chen 004; Theodore Leng; Luoluo Zheng; Lauren Kutzscher; Jeffrey J. Ma; Luis de Sisternes; Daniel L. Rubin (Medical Image Anal., 2013)

Application of Improved Homogeneity Similarity-Based Denoising in Optical Coherence Tomography Retinal Images. - Qiang Chen 004; Luis de Sisternes; Theodore Leng; Daniel L. Rubin (J. Digit. Imaging, 2015)

A Multi-Scale Deep Convolutional Neural Network For Joint Segmentation And Prediction Of Geographic Atrophy In SD-OCT Images. - Yuhan Zhang; Zexuan Ji; Sijie Niu; Theodore Leng; Daniel L. Rubin; Qiang Chen 004 (ISBI, 2019)

Geographic atrophy segmentation in SD-OCT images using synthesized fundus autofluorescence imaging. - Menglin Wu; Xinxin Cai; Qiang Chen 004; Zexuan Ji; Sijie Niu; Theodore Leng; Daniel L. Rubin; Hyunjin Park (Comput. Methods Programs Biomed., 2019)

A Deep-learning Approach for Prognosis of Age-Related Macular Degeneration Disease using SD-OCT Imaging Biomarkers. - Imon Banerjee; Luis de Sisternes; Joelle A. Hallak; Theodore Leng; Aaron Osborne; Mary Durbin; Daniel L. Rubin (CoRR, 2019)

Automatically Determining the Confocal Parameters From OCT B-Scans for Quantification of the Attenuation Coefficients. - Nicholas Dwork; Gennifer T. Smith; Theodore Leng; John M. Pauly; Audrey K. Bowden (IEEE Trans. Medical Imaging, 2019)

Data Quality Framework for Assessing Data from Electronic Health Record-Enabled Registries. - Amanda L. Lien; Rishabh Jain; Claire Margolis; Sam Haaf; Alex Koshta; Solmaz Bagherpour; Srikanth Kaja; David Budd; Andrew LaPrise; Kevin Wood; Theodore Leng; Matthew Roe; et al. (AMIA, 2020)

A Platform for Regulatory-Grade Evidence Generation from Routine Electronic Health Record Data Capture. - Claire A. Margolis; Chhaya Shadra; Alex Koshta; Cuau Leyva; Neha Seth; Solmaz Bagherpour; Rakesh Puthalath; Helene Fevrier; Amanda Lien; Rishabh Jain; Hariesh Rajasekar; Theodore Leng; et al. (AMIA, 2020)

MS-CAM: Multi-Scale Class Activation Maps for Weakly-Supervised Segmentation of Geographic Atrophy Lesions in SD-OCT Images. - Xiao Ma 011; Zexuan Ji; Sijie Niu; Theodore Leng; Daniel L. Rubin; Qiang Chen 004 (IEEE J. Biomed. Health Informatics, 2020)

An integrated time adaptive geographic atrophy prediction model for SD-OCT images. - Yuhan Zhang; Xiwei Zhang; Zexuan Ji; Sijie Niu; Theodore Leng; Daniel L. Rubin; Songtao Yuan; Qiang Chen 004 (Medical Image Anal., 2021)

Understanding Mechanisms of Missingness for Unspecified Diabetic Retinopathy Disease Severity in the Electronic Health Record: An IRIS® Registry Analysis. - Durga S. Borkar; Meghan Hatfield; Thaihien Nguyen; Richard Chapman; Theodore Leng; Michael Mbagwu; Matthew Roe; Shrujal Baxi; Aracelis Z. Torres (AMIA, 2022)

Contrastive learning-based pretraining improves representation and transferability of diabetic retinopathy classification models. - Minhaj Nur Alam; Rikiya Yamashita; Vignav Ramesh; Tejas S. Prabhune; Jennifer I. Lim; R. V. P. Chan; Joelle A. Hallak; Theodore Leng; Daniel L. Rubin (CoRR, 2022)

Identifying the mechanism of missingness for unspecified diabetic retinopathy disease severity in the electronic health record: an IRIS® Registry analysis. - Meghan Hatfield; Thai Hien Nguyen; Richard Chapman; Alayna C. Myrick; Theodore Leng; Michael Mbagwu; Shrujal Baxi; Aracelis Z. Torres; Durga S. Borkar (J. Am. Medical Informatics Assoc., 2023)

Quantitative Characterization of Retinal Features in Translated OCTA. - Rashadul Hasan Badhon; Atalie Carina Thompson; Jennifer I. Lim; Theodore Leng; Minhaj Nur Alam (CoRR, 2024)

Multi-OCT-SelfNet: Integrating Self-Supervised Learning with Multi-Source Data Fusion for Enhanced Multi-Class Retinal Disease Classification. - Fatema-E. Jannat; Sina Gholami; Jennifer I. Lim; Theodore Leng; Minhaj Nur Alam; Hamed Tabkhi (CoRR, 2024)

Mirrored X-Net: Joint classification and contrastive learning for weakly supervised GA segmentation in SD-OCT. - Zexuan Ji; Xiao Ma 011; Theodore Leng; Daniel L. Rubin; Qiang Chen 004 (Pattern Recognit., 2024)