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 Jul 19; 211860.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Duong MT, Rauschecker AM, Mohan S. Diverse Applications of Artificial Intelligence in Neuroradiology. Neuroimaging Clin N Am. 2020 Nov; 30(4):505-516.

Rauschecker AM, Rudie JD, Xie L, Wang J, Duong MT, Botzolakis EJ, Kovalovich AM, Egan J, Cook TC, Bryan RN, Nasrallah IM, Mohan S, Gee JC. Artificial Intelligence System Approaching Neuroradiologist-level Differential Diagnosis Accuracy at Brain MRI. Radiology. 2020 06; 295(3):626-637.

Bryan RN, Davatzikos C, Herskovits EH, Mohan S, Rudie JD, Rauschecker AM. Medical Image Analysis: Human and Machine. Acad Radiol. 2020 01; 27(1):76-81.

Rudie JD, Weiss DA, Saluja R, Rauschecker AM, Wang J, Sugrue L, Bakas S, Colby JB. Multi-Disease Segmentation of Gliomas and White Matter Hyperintensities in the BraTS Data Using a 3D Convolutional Neural Network. Front Comput Neurosci. 2019; 13:84.

Duong MT, Rauschecker AM, Rudie JD, Chen PH, Cook TS, Bryan RN, Mohan S. Artificial intelligence for precision education in radiology. Br J Radiol. 2019 Nov; 92(1103):20190389.

Duong MT, Rudie JD, Wang J, Xie L, Mohan S, Gee JC, Rauschecker AM. Convolutional Neural Network for Automated FLAIR Lesion Segmentation on Clinical Brain MR Imaging. AJNR Am J Neuroradiol. 2019 08; 40(8):1282-1290.

Rudie JD, Rauschecker AM, Bryan RN, Davatzikos C, Mohan S. Emerging Applications of Artificial Intelligence in Neuro-Oncology. Radiology. 2019 03; 290(3):607-618.

Silson EH, Aleman TS, Willett A, Serrano LW, Pearson DJ, Rauschecker AM, Maguire AM, Baker CI, Bennett J, Ashtari M. Comparing Clinical Perimetry and Population Receptive Field Measures in Patients with Choroideremia. Invest Ophthalmol Vis Sci. 2018 07 02; 59(8):3249-3258.

Rudie JD, Rauschecker AM, Nabavizadeh SA, Mohan S. Neuroimaging of Dilated Perivascular Spaces: From Benign and Pathologic Causes to Mimics. J Neuroimaging. 2018 03; 28(2):139-149.

Rauschecker AM, Levine MS, Whitson MJ, Tondon R, Rubesin SE, Furth EE, Metz DC. Esophageal Lichen Planus: Clinical and Radiographic Findings in Eight Patients. AJR Am J Roentgenol. 2017 Jan; 208(1):101-106.

Rauschecker AM, Cook TS. App Review Series: RadioGraphics. J Digit Imaging. 2016 06; 29(3):279-83.

Winawer J, Kay KN, Foster BL, Rauschecker AM, Parvizi J, Wandell BA. Asynchronous broadband signals are the principal source of the BOLD response in human visual cortex. Curr Biol. 2013 Jul 08; 23(13):1145-53.

Chen J, Dastjerdi M, Foster BL, LaRocque KF, Rauschecker AM, Parvizi J, Wagner AD. Human hippocampal increases in low-frequency power during associative prediction violations. Neuropsychologia. 2013 Oct; 51(12):2344-51.

Rauschecker AM, Patel CV, Yeom KW, Eisenhut CA, Gawande RS, O'Brien JM, Ebrahimi KB, Daldrup-Link HE. High-resolution MR imaging of the orbit in patients with retinoblastoma. Radiographics. 2012 Sep-Oct; 32(5):1307-26.

Yeatman JD, Rauschecker AM, Wandell BA. Anatomy of the visual word form area: adjacent cortical circuits and long-range white matter connections. Brain Lang. 2013 May; 125(2):146-55.

Rauschecker AM, Bowen RF, Parvizi J, Wandell BA. Position sensitivity in the visual word form area. Proc Natl Acad Sci U S A. 2012 Jun 12; 109(24):E1568-77.

Nune G, Winawer J, Rauschecker AM, Dastjerdi M, Foster BL, Wandell B, Parvizi J. Problem of signal contamination in interhemispheric dual-sided subdural electrodes. Epilepsia. 2011 Nov; 52(11):e176-80.

Rauschecker AM, Bowen RF, Perry LM, Kevan AM, Dougherty RF, Wandell BA. Visual feature-tolerance in the reading network. Neuron. 2011 Sep 08; 71(5):941-53.

Wandell BA, Rauschecker AM, Yeatman JD. Learning to see words. Annu Rev Psychol. 2012; 63:31-53.

Rauschecker AM, Dastjerdi M, Weiner KS, Witthoft N, Chen J, Selimbeyoglu A, Parvizi J. Illusions of visual motion elicited by electrical stimulation of human MT complex. PLoS One. 2011; 6(7):e21798.

Dastjerdi M, Foster BL, Nasrullah S, Rauschecker AM, Dougherty RF, Townsend JD, Chang C, Greicius MD, Menon V, Kennedy DP, Parvizi J. Differential electrophysiological response during rest, self-referential, and non-self-referential tasks in human posteromedial cortex. Proc Natl Acad Sci U S A. 2011 Feb 15; 108(7):3023-8.

Rauschecker AM, Pringle A, Watkins KE. Changes in neural activity associated with learning to articulate novel auditory pseudowords by covert repetition. Hum Brain Mapp. 2008 Nov; 29(11):1231-42.

Rauschecker AM, Deutsch GK, Ben-Shachar M, Schwartzman A, Perry LM, Dougherty RF. Reading impairment in a patient with missing arcuate fasciculus. Neuropsychologia. 2009 Jan; 47(1):180-94.

Rauschecker AM, Solomon SG, Glennerster A. Stereo and motion parallax cues in human 3D vision: can they vanish without a trace? J Vis. 2006 Dec 19; 6(12):1471-85.

Rauschecker AM, Bestmann S, Walsh V, Thilo KV. Phosphene threshold as a function of contrast of external visual stimuli. Exp Brain Res. 2004 Jul; 157(1):124-7.

Deep Learning to Predict Neonatal and Infant Brain Age from Myelination on Brain MRI Scans.

Radiology

Chen JV, Chaudhari G, Hess CP, Glenn OA, Sugrue LP, Rauschecker AM, Li Y

Automated multiclass tissue segmentation of clinical brain MRIs with lesions.

NeuroImage. Clinical

Weiss DA, Saluja R, Xie L, Gee JC, Sugrue LP, Pradhan A, Nick Bryan R, Rauschecker AM, Rudie JD

Interinstitutional Portability of a Deep Learning Brain MRI Lesion Segmentation Algorithm.

Radiology. Artificial intelligence

Rauschecker AM, Gleason TJ, Nedelec P, Duong MT, Weiss DA, Calabrese E, Colby JB, Sugrue LP, Rudie JD, Hess CP

Brainlab Publications

Tafasitamab at the blood-brain barrier.

Rauschecker AM, Mo SS, Randall M, Shen-Sampas J, Rubenstein JL. Tafasitamab at the blood-brain barrier. Br J Haematol. 2023 Jan 23.

Development of Gestational Age-Based Fetal Brain and Intracranial Volume Reference Norms Using Deep Learning.

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 Jan; 44(1):82-90.

The University of California San Francisco Preoperative Diffuse Glioma MRI Dataset.

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.

Longitudinal Assessment of Posttreatment Diffuse Glioma Tissue Volumes with Three-dimensional Convolutional Neural Networks.

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.

Deep Learning to Predict Neonatal and Infant Brain Age from Myelination on Brain MRI Scans.

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 Jul 19; 211860.

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).

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.

Application of a Domain-specific BERT for Detection of Speech Recognition Errors in Radiology Reports.

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.

Diagnostic Approach to Pulsatile Tinnitus: A Narrative Review.

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.

Combining radiomics and deep convolutional neural network features from preoperative MRI for predicting clinically relevant genetic biomarkers in glioblastoma.

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.

Corrigendum to "Microstructural development from 9 to 14 years: Evidence from the ABCD Study" [Dev. Cognit. Neurosci. 53 (2022) 101044].

Palmer CE, Pecheva D, Iversen JR, Hagler DJ, Sugrue L, Nedelec P, Fan CC, Thompson WK, Jernigan TL, Dale AM. Corrigendum to "Microstructural development from 9 to 14 years: Evidence from the ABCD Study" [Dev. Cognit. Neurosci. 53 (2022) 101044]. Dev Cogn Neurosci. 2022 Apr; 54:101063.

Microstructural development from 9 to 14 years: Evidence from the ABCD Study.

Palmer CE, Pecheva D, Iversen JR, Hagler DJ, Sugrue L, Nedelec P, Fan CC, Thompson WK, Jernigan TL, Dale AM. Microstructural development from 9 to 14 years: Evidence from the ABCD Study. Dev Cogn Neurosci. 2022 02; 53:101044.

Interinstitutional Portability of a Deep Learning Brain MRI Lesion Segmentation Algorithm.

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.

Detection of Neoplasms by Metagenomic Next-Generation Sequencing of Cerebrospinal Fluid.

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.

Automated multiclass tissue segmentation of clinical brain MRIs with lesions.

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.

Brain MRI Deep Learning and Bayesian Inference System Augments Radiology Resident Performance.

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.

Feasibility of Simulated Postcontrast MRI of Glioblastomas and Lower-Grade Gliomas by Using Three-dimensional Fully Convolutional Neural Networks.

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.

Rates of Incidental Findings in Brain Magnetic Resonance Imaging in Children.

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.

Three-dimensional U-Net Convolutional Neural Network for Detection and Segmentation of Intracranial Metastases.

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.

Subspecialty-Level Deep Gray Matter Differential Diagnoses with Deep Learning and Bayesian Networks on Clinical Brain MRI: A Pilot Study.

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.

Diverse Applications of Artificial Intelligence in Neuroradiology.

Duong MT, Rauschecker AM, Mohan S. Diverse Applications of Artificial Intelligence in Neuroradiology. Neuroimaging Clin N Am. 2020 Nov; 30(4):505-516.

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