Vinay A. Duddalwar, MD, FRCR
Vinay Duddalwar is currently the Section Chief of Abdominal Imaging at USC and the Medical Director, Imaging for the Norris Cancer Center at USC. He completed his medical education at Nagpur, radiology residencies at Pune, India and Aberdeen, UK and a fellowship in abdominal imaging and intervention at the University of British Columbia, Vancouver. He was on the faculty at Grampian University NHS Hospitals in Aberdeen UK and then subsequently moved to USC.
His interests are in the field of abdominal oncologic imaging, especially genitourinary imaging and radiomics. His research focus is in the field of renal mass imaging, including contrast enhanced ultrasound, as well as quantitative imaging. He has funded research currently ongoing in these areas. He has presented over a 100 abstracts at scientific meetings and has authored a number of peer reviewed articles, reviews, and book chapters. He is an active member of a number of national and international radiology societies. He is a GU section editor for Clinical Radiology as well as reviewer for a number of radiology and urology journals.
Google Scholar: https://scholar.google.com.tw/citations?user=Up-ZE4cAAAAJ&hl=en
CTSI Profile: http://profiles.sc-ctsi.org/vinay.duddalwar#toc-id2
Bino A. Varghese, PhD
Bino Varghese is an Assistant Professor of Research with expertise in imaging, image processing, quantification and biomechanics. He obtained his B.E. in Medical Electronics from Visveswariah Technological University in 2002 and his Master's degree in Biomedical Engineering with a focus in imaging and image processing, from the Wright State University at Dayton, Ohio in 2005. In 2010, he received his Ph.D. in Biomedical Sciences from Wright State University. His doctoral dissertation was titled "Quantitative Computed-Tomography Based Bone-Strength Indicators for the Identification of Low Bone-Strength Individuals in a Clinical Environment."
In Feb 2014, he joined the Department of Radiology at USC as a Research Laboratory Specialist. His current work focuses on investigating the technical feasibility and clinical value of quantifying multi-modal imaging biomarkers across various domains with an aim to maximize data utilization and increase clinical translation.
Google Scholar: https://scholar.google.com/citations?user=gD0AIZAAAAAJ&hl=en
Bhushan Desai, MBBS, MS
Bhushan_Desai is an Assistant Professor and Director of Clinical Research in the Department of Radiology at the Keck School of Medicine of USC. He completed his MD training in India in 2007 and joined the Keck School of Medicine of USC to gain specialized training in clinical research with focus on patient oriented translational research. He has extensive practical experience in imaging research (presented thesis based on NIH R01 project, "(Role of FDG PET/CT in Prostate Cancer)" and has been involved in several multidisciplinary research projects in collaborations with colleagues in the Department of Radiology as well as other departments at KSOM and other schools at USC. He also closely work with several junior and senior faculty members in the Department of Radiology and helps them write research proposals which can lead to grant funding. He also successfully mentors junior faculty members and medical students in various aspects of research and helps them get research grants and scholarships. medical students in various aspects of research and helps them get research grants and scholarships.
As Director of the Clinical Research Program in the Department of Radiology, his mission is to provide resources for clinical/translational research that are innovative and cutting edge.
USC Webpage: http://www-hsc.usc.edu/~bhushand/
Darryl H. Hwang, PhD
Darryl Hwang is an Assistant Professor of Research and Director of the 4D Quantitative Imaging Lab in the Department of Radiology at the Keck School of Medicine of USC. He is a life-long Trojan, obtaining his Bachelor of Science in Biomedical Engineering (emphasis in Biochemical Engineering), Master of Science in Biomedical Engineering (Medical Imaging and Imaging Informatics), and Doctor of Philosophy from University of Southern California. His past experiences range a broad swath of science and engineering, including DNA computing, technology start-ups, science education, and autism information distribution.
He is actively engaged in clinical translational research by providing technical expertise in medical image processing, software development, and workflow automation and optimization. His research interests pertain to the application of quantitative algorithms and efficient processing to all divisions and modality in radiology.
Google Scholar: https://scholar.google.com/citations?user=Sd4hREoAAAAJ&hl=en
Steven Cen, PhD
Dr. Cen has extensive research experience in database and statistics with application in imaging study and clinical trial. He is the statistical advisor of BMJ-Heart Editorial Board, and the in-house lead biostatistician for Dept. of Neurology and Dept. of Radiology at USC Keck School of Medicine. Currently, he serves as the lead statistician of two large NIH funded studies: Low-Cost Portable Computer-Aided Diagnosis Ultrasound System for Breast Cancer Triage in Low to Middle-Income Countries (LMIC) Environments, and Human Connectomes for Low Vision, Blindness, and Sight Restoration.
He also served as the co-director of Data Management and Analysis Center (DMAC) for two NIH funded multi-center landmark phase III clinical trials in stroke rehabilitation history - Locomotor Experience Applied Post-Stroke (LEAPS) Trial and Interdisciplinary Comprehensive Arm Rehabilitation Evaluation Stroke Initiative (I-CARE) Trial. He is also the director of Data Management and Informatics core for a large California State funded dental health service project (USC-CHAMP) at the Herman Ostrow School of Dentistry, University of Southern California.
Salford Systems: http://www.salford-systems.com/
Felix Y. Yap, MD
Felix is currently a second-year diagnostic radiology resident at the University of Southern California. Radiology's unique roots in mathematics, physics, and engineering are the basis underlying our field's objective and reproducible methods for diagnosing disease. In this same spirit, he aims to validate the use of quantitative shape metrics as a biomarker for noninvasively differentiating benign from malignant renal tumors. In addition to his radiology training, he possess a biomedical engineering background, with expertise in MATLAB and quantitative image analysis.
In two previous projects at Duke University and University of Illinois at Chicago, he designed computerized algorithms that can efficiently analyze large cohorts of images and extract the targeted quantitative information:
(1) colorimetric analysis to calculate the amount of fibrosis on a histology slide specimen, and
(2) shape analysis to quantify the morphologic irregularity of hepatic tumors on cross-sectional imaging.
Ting-wei Fan (Justin)
Ting-wei is a 4th year medical student at Keck School of Medicine of USC.
He completed his undergraduate with a BS in Biological Sciences at USC Dana and David Dornsife College of Letters, Arts and Sciences.
Previously, Ting-wei has experience working as a research assistant in USC Division of Biokinesiology and Physical Therapy for projects involving accelerometer analysis in hemiparetic stroke patients.
Ting-wei’s research interests involve the uses of contrast-enhanced computerized tomography in differentiating between variants of bladder cancers. Specifically, using radiomic texture analysis data to distinguish micropapillary carcinomas and transitional cell carcinomas.
Christopher is a 4th year USC medical student and will be applying to diagnostic radiology residency programs in the Fall of 2018.
Prior to joining USC, Christopher received his BS in Molecular Environmental Biology from UC Berkeley. Additionally, he has worked as a research assistant at Stanford University School of Medicine’s Radiology Department studying a novel PET radiotracer’s ability to detect a molecular receptor believed to be involved in pain transmission in in vivo models.
Christopher’s research interests involve the development of radiomic techniques to improve imaging diagnosis. Some of the projects that he is working on invovles integrating epigenomic data with texture features to better enhance diagnosis of clear cell renal cell carcinoma and comparing radiomics metrics to differentiate type 2 papillary carcinoma from renal cell carcinomas.
Maria Elena Rivas
Maria Elena Rivas received her medical degree at the University of El Salvador, El Salvador. She completed a radiology residency at Instituto Salvadoreno del Seguro Social, and has valuable background in general surgery as well.
Her research interest is in abdominal and oncology imaging. Currently as part of the USC Radiomics laboratory, she is working on projects applying Radiomics to urogenital imaging data, particularly those assessing the potential of Radiomics to enable differentiation of malignant tumors with similar imaging characteristics but differ in their aggressiveness, therefore improving early diagnosis and treatment.
Xiaomeng Lei (Emma)
Xiaomeng Lei is a Statistician in the Department of Radiology at the Keck School of Medicine of USC.
She completed her MPH (master of public health) degree in Claremont Graduate University (CGU) in May 2017, concentrated in Applied Biostatistics and Epidemiology.
Previously, Xiaomeng has experience working as a field manager, which is promoted from research assistant in School of Community and Global Health in CGU involving in intervention project targeted on Chinese Americans with Type II Diabetes.
She also has spent several years developing her skills in data management through SAS. She is actively engaged in data manipulation, data analysis and data management for clinic research in Radiology Department.
- Chidubem Ugwueze,
- Mike Kwon,
- Megha Nayyar,
- Michael Chang,
- Christopher Deng,
- Qi Wang,
- Yanwen Xi,
- Soumya Da,
- Tania Gill,
- Chinmay Jog