BRAIN Lab Publications

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.

Artificial Intelligence System Approaching Neuroradiologist-level Differential Diagnosis Accuracy at Brain MRI.

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.

Medical Image Analysis: Human and Machine.

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.

Multi-Disease Segmentation of Gliomas and White Matter Hyperintensities in the BraTS Data Using a 3D Convolutional Neural Network.

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.

Artificial intelligence for precision education in radiology.

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.

Convolutional Neural Network for Automated FLAIR Lesion Segmentation on Clinical Brain MR Imaging.

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.

Emerging Applications of Artificial Intelligence in Neuro-Oncology.

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.

Comparing Clinical Perimetry and Population Receptive Field Measures in Patients with Choroideremia.

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.

Neuroimaging of Dilated Perivascular Spaces: From Benign and Pathologic Causes to Mimics.

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.

Esophageal Lichen Planus: Clinical and Radiographic Findings in Eight Patients.

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.

App Review Series: RadioGraphics.

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

Pages