Joseph Yuan-Chieh Lo
Professor in Radiology
My research is at the intersection of computer vision, machine learning, and medical imaging, with a dual focus on mammography and computed tomography (CT). Together with our industry partner, we developed deep learning algorithms for breast cancer screening with 2D/3D mammography, and that product is now undergoing FDA approval with anticipated rollout to clinics worldwide. We also pioneer the creation of "digital twin" anatomical models from patient imaging data, using these models to forge new paths in CT scan analysis through virtual readers and deep learning techniques. Additionally, we're developing a computer-aided triage system for detecting diseases across multiple organs in body CT scans, leveraging hospital-scale datasets and integrating natural language processing with deep learning for comprehensive disease classification.
Appointments and Affiliations
- Professor in Radiology
- Professor of Biomedical Engineering
- Professor in the Department of Electrical and Computer Engineering
- Member of the Duke Cancer Institute
- Office Location: 2424 Erwin Road, Suite 302, Ravin Advanced Imaging Labs, Durham, NC 27705
- Office Phone: (919) 684-7763
- Email Address: firstname.lastname@example.org
- Duke University, 1995
- Ph.D. Duke University, 1993
- B.S.E.E. Duke University, 1988
- RROMP 301B: Radiology, Radiation Oncology & Medical Physics
In the News
- The First AI Breast Cancer Sleuth That Shows Its Work (Jan 20, 2022 | Pratt School of Engineering)
- Tushar, FI; D'Anniballe, VM; Hou, R; Mazurowski, MA; Fu, W; Samei, E; Rubin, GD; Lo, JY, Classification of Multiple Diseases on Body CT Scans Using Weakly Supervised Deep Learning., Radiology: Artificial Intelligence, vol 4 no. 1 (2022) [10.1148/ryai.210026] [abs].
- Grimm, LJ; Neely, B; Hou, R; Selvakumaran, V; Baker, JA; Yoon, SC; Ghate, SV; Walsh, R; Litton, TP; Devalapalli, A; Kim, C; Soo, MS; Hyslop, T; Hwang, ES; Lo, JY, Mixed-Methods Study to Predict Upstaging of DCIS to Invasive Disease on Mammography., Ajr. American Journal of Roentgenology, vol 216 no. 4 (2021), pp. 903-911 [10.2214/AJR.20.23679] [abs].
- Draelos, RL; Dov, D; Mazurowski, MA; Lo, JY; Henao, R; Rubin, GD; Carin, L, Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes., Med Image Anal, vol 67 (2021) [10.1016/j.media.2020.101857] [abs].
- Abadi, E; Segars, WP; Tsui, BMW; Kinahan, PE; Bottenus, N; Frangi, AF; Maidment, A; Lo, J; Samei, E, Virtual clinical trials in medical imaging: a review., Journal of Medical Imaging (Bellingham, Wash.), vol 7 no. 4 (2020) [10.1117/1.JMI.7.4.042805] [abs].
- Hou, R; Mazurowski, MA; Grimm, LJ; Marks, JR; King, LM; Maley, CC; Hwang, E-SS; Lo, JY, Prediction of Upstaged Ductal Carcinoma In Situ Using Forced Labeling and Domain Adaptation., Ieee Trans Biomed Eng, vol 67 no. 6 (2020), pp. 1565-1572 [10.1109/TBME.2019.2940195] [abs].
- Georgian-Smith, D; Obuchowski, NA; Lo, JY; Brem, RF; Baker, JA; Fisher, PR; Rim, A; Zhao, W; Fajardo, LL; Mertelmeier, T, Can Digital Breast Tomosynthesis Replace Full-Field Digital Mammography? A Multireader, Multicase Study of Wide-Angle Tomosynthesis., Ajr. American Journal of Roentgenology, vol 212 no. 6 (2019), pp. 1393-1399 [10.2214/AJR.18.20294] [abs].
- Rossman, AH; Catenacci, M; Zhao, C; Sikaria, D; Knudsen, JE; Dawes, D; Gehm, ME; Samei, E; Wiley, BJ; Lo, JY, Three-dimensionally-printed anthropomorphic physical phantom for mammography and digital breast tomosynthesis with custom materials, lesions, and uniform quality control region., Journal of Medical Imaging (Bellingham, Wash.), vol 6 no. 2 (2019) [10.1117/1.JMI.6.2.021604] [abs].
- Sturgeon, GM; Park, S; Segars, WP; Lo, JY, Synthetic breast phantoms from patient based eigenbreasts., Med Phys, vol 44 no. 12 (2017), pp. 6270-6279 [10.1002/mp.12579] [abs].
- Ikejimba, L; Lo, JY; Chen, Y; Oberhofer, N; Kiarashi, N; Samei, E, A quantitative metrology for performance characterization of five breast tomosynthesis systems based on an anthropomorphic phantom., Med Phys, vol 43 no. 4 (2016) [10.1118/1.4943373] [abs].
- Erickson, DW; Wells, JR; Sturgeon, GM; Samei, E; Dobbins, JT; Segars, WP; Lo, JY, Population of 224 realistic human subject-based computational breast phantoms., Med Phys, vol 43 no. 1 (2016) [10.1118/1.4937597] [abs].