Research Summary

Dr. Andreas Rauschecker is a neuroradiologist who cares for both adults and children. He specializes in using advanced imaging technologies, such as CT and MRI, to diagnose nervous system disorders. He also treats patients by means of image-guided procedures and uses his expertise to assist colleagues in managing and treating their patients.

In research, Rauschecker focuses on using modern technology to understand the brain in conditions of health and disease. Specifically, he uses artificial intelligence and advanced image-processing techniques to investigate the brain and its appearance in relation to disease, with the goal of improving the information he can provide to patients and other doctors.

Education

Fellowship in Neuroradiology, 06/2020 - Neuroradiology, University of California, San Francisco
02/2020 - Diversity, Equity, and Inclusion Champion Training, University of California
Residency, 06/2018 - Diagnostic Radiology, University of Pennsylvania
MD PhD, 06/2013 - Neuroscience, Medical School, Stanford University
M.Sc., 08/2005 - Neuroscience, Oxford University
B.S., 06/2004 - Biology & Psychology, Georgetown University

Honors & Awards

  • ASNR Trainee Award, 2020
  • RSNA Research Scholar Award, 2020
  • ASNR/ASfNR MIT-E Scholarship, 2019
  • RSNA Roentgen Fellow Research Award, 2019
  • Roger A. Bauman, MD Award, SIIM, 2019
  • ACR-AUR Research Scholar Program, 2018
  • NVIDIA GPU Seed Grant, 2018
  • RSNA Roentgen Resident Research Award, 2018
  • RSNA Resident Research Grant, 2017
  • RSNA Magna Cum Laude Award, 2016
  • RSNA Certificate of Merit Award, 2015
  • Mary Duke Biddle Clinical Scholars Program, Stanford University, 2013
  • Stanford Bio-X Graduate Student Fellowship, Stanford University, 2008
  • Clarendon Fund Scholarship, Oxford University, 2004
  • Howard Hughes Undergraduate Research Scholar, Georgetown University, 2000-2004

Selected Publications

  1. George E, Rauschecker AM. Beyond the AJR: Deep Learning Shows Promise in the Detection of Retinal Hemorrhage on Pediatric Head CT. AJR Am J Roentgenol. 2023 Aug 23.  View on PubMed
  2. LaBella D, Adewole M, Alonso-Basanta M, Altes T, Anwar SM, Baid U, Bergquist T, Bhalerao R, Chen S, Chung V, Conte GM, Dako F, Eddy J, Ezhov I, Godfrey D, Hilal F, Familiar A, Farahani K, Iglesias JE, Jiang Z, Johanson E, Kazerooni AF, Kent C, Kirkpatrick J, Kofler F, Leemput KV, Li HB, Liu X, Mahtabfar A, McBurney-Lin S, McLean R, Meier Z, Moawad AW, Mongan J, Nedelec P, Pajot M, Piraud M, Rashid A, Reitman Z, Shinohara RT, Velichko Y, Wang C, Warman P, Wiggins W, Aboian M, Albrecht J, Anazodo U, Bakas S, Flanders A, Janas A, Khanna G, Linguraru MG, Menze B, Nada A, Rauschecker AM, Rudie J, Tahon NH, Villanueva-Meyer J, Wiestler B, Calabrese E. The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma. ArXiv. 2023 May 12.  View on PubMed
  3. Pham N, Hill V, Rauschecker A, Lui Y, Niogi S, Fillipi CG, Chang P, Zaharchuk G, Wintermark M. Critical Appraisal of Artificial Intelligence-Enabled Imaging Tools Using the Levels of Evidence System. AJNR Am J Neuroradiol. 2023 05; 44(5):E21-E28.  View on PubMed
  4. Rauschecker AM, Mo SS, Randall M, Shen-Sampas J, Rubenstein JL. Tafasitamab at the blood-brain barrier. Br J Haematol. 2023 04; 201(1):154-157.  View on PubMed
  5. Tran CBN, Nedelec P, Weiss DA, Rudie JD, Kini L, Sugrue LP, Glenn OA, Hess CP, Rauschecker AM. Development of Gestational Age-Based Fetal Brain and Intracranial Volume Reference Norms Using Deep Learning. AJNR Am J Neuroradiol. 2023 01; 44(1):82-90.  View on PubMed
  6. Calabrese E, Villanueva-Meyer JE, Rudie JD, Rauschecker AM, Baid U, Bakas S, Cha S, Mongan JT, Hess CP. The University of California San Francisco Preoperative Diffuse Glioma MRI Dataset. Radiol Artif Intell. 2022 Nov; 4(6):e220058.  View on PubMed
  7. Rudie JD, Calabrese E, Saluja R, Weiss D, Colby JB, Cha S, Hess CP, Rauschecker AM, Sugrue LP, Villanueva-Meyer JE. Longitudinal Assessment of Posttreatment Diffuse Glioma Tissue Volumes with Three-dimensional Convolutional Neural Networks. Radiol Artif Intell. 2022 Sep; 4(5):e210243.  View on PubMed
  8. Chen JV, Chaudhari G, Hess CP, Glenn OA, Sugrue LP, Rauschecker AM, Li Y. Deep Learning to Predict Neonatal and Infant Brain Age from Myelination on Brain MRI Scans. Radiology. 2022 Dec; 305(3):678-687.  View on PubMed
  9. Kline C, Stoller S, Byer L, Samuel D, Lupo JM, Morrison MA, Rauschecker AM, Nedelec P, Faig W, Dubal DB, Fullerton HJ, Mueller S. An Integrated Analysis of Clinical, Genomic, and Imaging Features Reveals Predictors of Neurocognitive Outcomes in a Longitudinal Cohort of Pediatric Cancer Survivors, Enriched with CNS Tumors (Rad ART Pro). Front Oncol. 2022; 12:874317.  View on PubMed
  10. Chaudhari GR, Liu T, Chen TL, Joseph GB, Vella M, Lee YJ, Vu TH, Seo Y, Rauschecker AM, McCulloch CE, Sohn JH. Application of a Domain-specific BERT for Detection of Speech Recognition Errors in Radiology Reports. Radiol Artif Intell. 2022 Jul; 4(4):e210185.  View on PubMed
  11. Narsinh KH, Hui F, Saloner D, Tu-Chan A, Sharon J, Rauschecker AM, Safoora F, Shah V, Meisel K, Amans MR. Diagnostic Approach to Pulsatile Tinnitus: A Narrative Review. JAMA Otolaryngol Head Neck Surg. 2022 05 01; 148(5):476-483.  View on PubMed
  12. Calabrese E, Rudie JD, Rauschecker AM, Villanueva-Meyer JE, Clarke JL, Solomon DA, Cha S. Combining radiomics and deep convolutional neural network features from preoperative MRI for predicting clinically relevant genetic biomarkers in glioblastoma. Neurooncol Adv. 2022 Jan-Dec; 4(1):vdac060.  View on PubMed
  13. Rauschecker AM, Gleason TJ, Nedelec P, Duong MT, Weiss DA, Calabrese E, Colby JB, Sugrue LP, Rudie JD, Hess CP. Interinstitutional Portability of a Deep Learning Brain MRI Lesion Segmentation Algorithm. Radiol Artif Intell. 2022 Jan; 4(1):e200152.  View on PubMed
  14. Gu W, Rauschecker AM, Hsu E, Zorn KC, Sucu Y, Federman S, Gopez A, Arevalo S, Sample HA, Talevich E, Nguyen ED, Gottschall M, Nourbakhsh B, Gold CA, Cree BAC, Douglas VC, Richie MB, Shah MP, Josephson SA, Gelfand JM, Miller S, Wang L, Tihan T, DeRisi JL, Chiu CY, Wilson MR. Detection of Neoplasms by Metagenomic Next-Generation Sequencing of Cerebrospinal Fluid. JAMA Neurol. 2021 11 01; 78(11):1355-1366.  View on PubMed
  15. Weiss DA, Saluja R, Xie L, Gee JC, Sugrue LP, Pradhan A, Nick Bryan R, Rauschecker AM, Rudie JD. Automated multiclass tissue segmentation of clinical brain MRIs with lesions. Neuroimage Clin. 2021; 31:102769.  View on PubMed
  16. Rudie JD, Duda J, Duong MT, Chen PH, Xie L, Kurtz R, Ware JB, Choi J, Mattay RR, Botzolakis EJ, Gee JC, Bryan RN, Cook TS, Mohan S, Nasrallah IM, Rauschecker AM. Brain MRI Deep Learning and Bayesian Inference System Augments Radiology Resident Performance. J Digit Imaging. 2021 08; 34(4):1049-1058.  View on PubMed
  17. Calabrese E, Rudie JD, Rauschecker AM, Villanueva-Meyer JE, Cha S. Feasibility of Simulated Postcontrast MRI of Glioblastomas and Lower-Grade Gliomas by Using Three-dimensional Fully Convolutional Neural Networks. Radiol Artif Intell. 2021 Sep; 3(5):e200276.  View on PubMed
  18. Li Y, Thompson WK, Reuter C, Nillo R, Jernigan T, Dale A, Sugrue LP, ABCD Consortium, Brown J, Dougherty RF, Rauschecker A, Rudie J, Barch DM, Calhoun V, Hagler D, Hatton S, Tanabe J, Marshall A, Sher KJ, Heeringa S, Hermosillo R, Banich MT, Squeglia L, Bjork J, Zucker R, Neale M, Herting M, Sheth C, Huber R, Reeves G, Hettema JM, Howlett KD, Cloak C, Baskin-Sommers A, Rapuano K, Gonzalez R, Karcher N, Laird A, Baker F, James R, Sowell E, Dick A, Hawes S, Sutherland M, Bagot K, Bodurka J, Breslin F, Morris A, Paulus M, Gray K, Hoffman E, Weiss S, Rajapakse N, Glantz M, Nagel B, Ewing SF, Goldstone A, Pfefferbaum A, Prouty D, Rosenberg M, Bookheimer S, Tapert S, Infante M, Jacobus J, Giedd J, Shilling P, Wade N, Uban K, Haist F, Heyser C, Palmer C, Kuperman J, Hewitt J, Cottler L, Isaiah A, Chang L, Edwards S, Ernst T, Heitzeg M, Puttler L, Sripada C, Iacono W, Luciana M, Clark D, Luna B, Schirda C, Foxe J, Freedman E, Mason M, McGlade E, Renshaw P, Yurgelun-Todd D, Albaugh M, Allgaier N, Chaarani B, Potter A, Ivanova M, Lisdahl K, Do E, Maes H, Bogdan R, Anokhin A, Dosenbach N, Glaser P, Heath A, Casey BJ, Gee D, Garavan HP, Dowling G, Brown S. Rates of Incidental Findings in Brain Magnetic Resonance Imaging in Children. JAMA Neurol. 2021 05 01; 78(5):578-587.  View on PubMed
  19. Rudie JD, Weiss DA, Colby JB, Rauschecker AM, Laguna B, Braunstein S, Sugrue LP, Hess CP, Villanueva-Meyer JE. Three-dimensional U-Net Convolutional Neural Network for Detection and Segmentation of Intracranial Metastases. Radiol Artif Intell. 2021 May; 3(3):e200204.  View on PubMed
  20. Rudie JD, Rauschecker AM, Xie L, Wang J, Duong MT, Botzolakis EJ, Kovalovich A, Egan JM, Cook T, Bryan RN, Nasrallah IM, Mohan S, Gee JC. Subspecialty-Level Deep Gray Matter Differential Diagnoses with Deep Learning and Bayesian Networks on Clinical Brain MRI: A Pilot Study. Radiol Artif Intell. 2020 Sep; 2(5):e190146.  View on PubMed

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