Imaging (AP, Breast, Neuro, Path, Thoracic) - Mass General Brigham Data Science Office

Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT

Robinson-Weiss C, Patel J, Bizzo BC, Glazer DI, Bridge CP, Andriole KP, Dabiri B, Chin JK, Dreyer K, Kalpathy-Cramer J, Mayo-Smith WW

2022

September 22, 2022

Large Scale Model Validation in Healthcare

Bridge CP, Fredriksson A, Guan J, Bryson S, Hillis JM, Mercaldo S, Morley RJ, Li MD, Li X, L’Italien E, Sack D, Zhong A, Dreyer KJ, Flores M, Kalpathy-Cramer J, Li Q, Lamb LR, Lehman CD, Schultz T, Andriole KP, Compas C, Bizzo BC, Haukioka R

Whitepaper

September 8, 2022

Predictive values of AI-based triage model in suboptimal CT pulmonary angiography

Ebrahimian S, Digumarthy SR, Homayounieh F, Bizzo BC, Dreyer KJ, Kalra MK.

Clinical Imaging, Volume 86, 2022, Pages 25-30, ISSN 0899-7071.

April 7, 2022

Development and Clinical Application of a Deep Learning Model to Identify Acute Infarct on Magnetic Resonance Imaging

Bridge CP, Bizzo BC, Hillis JM, et al.

Sci Rep 12, 2154 (2022)

February 9, 2022

A Fully Automated Deep Learning Pipeline for Multi–Vertebral Level Quantification and Characterization of Muscle and Adipose Tissue on Chest CT Scans

Bridge CP, Best TD, Wrobel MM, Marquardt JP, Magudia K, Javidan C, Chung J, Kalpathy-Cramer J, Andriole KP, Fintelmann RJ.

Radiology: AI. (in press). 2022

January 5, 2022

Lessons Learned From the Front Lines of Artificial Intelligence Implementation

Alkasab TK, Bizzo BC.

J Am Coll Radiol. 2021 Nov;18(11):1474-1475. doi: 10.1016/j.jacr.2021.09.019. Epub 2021 Oct 9. PMID: 34637776

October 9, 2021

Data Management in Artificial Intelligence-Assisted Radiology Reporting

Bizzo BC, Almeida RR, Alkasab TK.

J Am Coll Radiol. 2021 Nov;18(11):1485-1488. doi: 10.1016/j.jacr.2021.09.017. Epub 2021 Oct 6. PMID: 34624236

October 6, 2021

The Trials and Tribulations of Assembling Large Medical Imaging Datasets for Machine Learning

Magudia K, Bridge CP, Andriole KP, Rosenthal MH.

Journal of Digital Imaging 2021

October 4, 2021

The Composite Severity Score for Lumbar Spine MRI: a Metric of Cumulative Degenerative Disease Predicts Time Spent on Interpretation and Reporting

Caton MT, Wiggins WF, Pomerantz SR, Andriole KP.

Journal of Digital Imaging 2021

May 23, 2021

A Deep Learning-based Model for Detecting Abnormalities on Brain MRI for Triaging: Preliminary Results from a Multi-site Experience

Gauriau R, Bizzo BC, Kitamura FC, Junior OL, Ferraciolli SF, Macruz FB, Sanchez TA, Garcia MRT, Vedolin LM, Dominques RC, Gasparetto EL, Andriole KP.

Radiology: Artificial Intelligence. Online April 21, 2021

April 21, 2021

Effects of age and sex on the distribution and symmetry of lumbar spinal and neural foraminal stenosis: a natural language processing analysis of 43,255 lumbar MRI reports

Caton MT, Wiggins WF, Pomerantz SR, Andriole KP

Neuroradiology. 2021;63:959–966

February 16, 2021

Computer-Assisted Reporting and Decision Support (CAR-DS) Increases Compliance with Follow-up Imaging and Hormonal Screening of Adrenal Incidentalomas

Almeida RR, Bizzo BC, Singh R, Andriole KP, Alkasab T.

Academic Radiology. Online February 12, 2021

February 12, 2021

Population-scale CT-based body composition analysis of a large, previously healthy outpatient population using deep learning to derive age, gender and race specific reference curves

Magudia K, Bridge CP, Bay CP, Babic A, Fintelmann FJ, Troschel FM, Miskin N, Wrobel WC, Brais LK, Andriole KP, Wolpin BM, Rosenthal MH.

Radiology 2021; 298(2):319-329

November 24, 2020

A Conference-Friendly, Hands-On Introduction to Deep Learning for Radiology Trainees

Wiggins WF, Caton MT, Magudia K, Rosenthal MH, Andriole KP.

Radiology: AI Nov 2020

November 4, 2020

Lumbar MRI Reporting Efficiency for Trainees over the Academic Year: An Opportunity for Improving Clinical Workflows in Academic Medical Centers

Caton MT, Wiggins WF, Pomerantz SR, Andriole KP.

J Am Coll Radiol. 2021;18:428–434

September 8, 2020

Initial Experience Integrating a Hands-On Innovation Curriculum into a Radiology Residency Program and Department

Succi MD, Zamarron BF, Fintlemann FJ, Andriole KP, Ottensmeyer MP, Whitehead DC, Harris GJ, McLoud TC, Brink JA, Gee MS, Uppot RN.

Journal of the American College of Radiology: JACR 17(10)1329-1333. April 17, 2020

April 17, 2020

An Overview and Case Study of the Clinical AI Model Development life Cycle for Healthcare Systems

Lu C, Wright B, Stout J, Gauriau R, Macruz F, Buch V, Andriole KP.

ICLR 2020 AI for Affordable Healthcare##. In Press 2020

March 26, 2020

Using DICOM Metadata for Radiological Image Series Categorization: A Feasibility Study on Large Clinical Brain MRI Datasets

Gauriau R, Bridge CP, Chen L, Kitamura F, Tenenholtz NA, Kirsch JE, Andriole KP, Michalski MH, Bizzo BC.

Journal of Digital Imaging 2020; 1-16

January 16, 2020

DeepAAA: Clinically Applicable and Generalizable Detection of Abdominal Aortic Aneurysm Using Deep Learning

Lu JT, Brooks R, Hahn S, Chen J, Buch JV, Kotecha G, Andriole KP, Ghoshhajra B, Pinto J, Vozila P, Michalski MH, Tenenholtz N.

MICCAI 2019 Lecture Notes in Computer Science, vol 11765, pp 723-731

October 10, 2019

The RSNA Pediatric Bone Age Machine Learning Challenge

Halabi SS, Prevedello LM, Kalpathy-Cramer J, Mamonov AB, Bilbily A, Cicero M, Pan I, Pereira LA, Sousa RT, Abdala N, Kitamura FC, Thodberg HH, Chen L, Shih G, Andriole KP, Kohli MD, Erickson BJ, Flanders AE.

Radiology. 2019 Feb;290(2):498-503. doi: 10.1148/radiol.2018180736. Epub 2018 Nov 27. PMID:30480490

February 2, 2019

Deep Learning for Acute Ischemic Stroke on Diffusion MRI: Performance Analysis in a Consecutive Cohort

Bizzo B, Bridge C, Gauriau R, Wiggins WF, Caton MT, Hillis J, Wright B, Tenenholtz NA, Andriole KP, Michalski M, Gonzalez RG.

Stroke vol. 50, February 2019

January 30, 2019

Interpretable Deep Learning-Based Characterization of Intracranial Hemorrhage on Head CT

Bizzo B, Hashemian B, McNitt T, Caton MT, Wiggins WF, Hillis J, Tenenholtz NA, Kitamura F, Gonzalez RG, Michalski M, Andriole KP, Pomerantz SR.

Stroke vol. 50, February 2019

January 30, 2019

Challenges Related to Artificial Intelligence Research in Medical Imaging and the Importance of Image Analysis Competitions

Prevedello LM, Halabi SS, Shih G, Wu, CC, Kohli MD, Chokshi, Erickson BJ, Kalpathy-Cramer J, Andriole KP, Flanders AE.

Radiology: Artificial Intelligence 2019, Published Online:Jan 30 2019

January 30, 2019

The Need for a Machine Learning Curriculum for Radiologists

Wood MJ, Tenenholtz NA, Geis JR, Michalski MH, Andriole KP.

J Am Coll Radiol. 2018; 740-742. pii: S1546-1440(18)31300-0. doi: 10.1016/j.jacr.2018.10.008. Epub 2018 October PMID:30528932

December 7, 2018

Implementing the DICOM Standard for Digital Pathology

Herrmann MD, Clunie DA, Fedorov A, Doyle SW, Pieper S, Klepeis V, Le LP, Mutter GL, Milstone DS, Schultz TJ, Kikinis R, Kotecha GK, Hwang DH, Andriole KP, Iafrate AJ, Brink JA, Boland GW, Dreyer KJ, Michalski M, Golden JA, Louis DN, Lennerz JK.

J Pathol Inform. 2018 Nov 2;9:37. doi: 10.4103/jpi.jpi_42_18. eCollection 2018. PMID: 30533276

November 2, 2018

Fully Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks

Bridge CP, Rosenthal M, Wright B, Kotecha GK, Fintelmann F, Troschel F, Miskin N, Desai K, Wrobel W, Babic A, Khalaf N, Brais L, Welch M, Zellers C, Tenenholtz N, Michalski MH, Wolpin B, Andriole KP.

MICCAI Workshop on Clinical Image-Based Procedures: Translational Research in Medical Imaging. CLIP Lecture Notes in Computer Science, vol 11041:204-213, Epub. 2018 October 2. Springer, Cham

October 2, 2018

Detection and Delineation of Acute Cerebral Infarct on DWI using Weakly Supervised Machine Learning

Pedemonte S, Bizzo B, Pomerantz SR, Tenenholtz N, Wright B, Walters M, Doyle S, McCarthy A, De Almeida RR, Andriole KP, Michalski MH, Gonzalez RG.

MICCAI 2018. Lecture Notes in Computer Science, vol 11072

September 13, 2018

Medical Image Synthesis for Data Augmentation and Anonymization Using Generative Adversarial Networks

Shin HC, Tenenholtz NA, Rogers JK, Schwartz CG, Senjem ML, Gunter JL, Andriole KP, Michalski MH.

MICCAI Workshop on Simulation and Synthesis in Medical Imaging SASHIMI 2018 Sept 12

September 12, 2018

Deep Spine: Automated Lumbar Vertebral Segmentation, Disc-level Designation and Spinal Stenosis Grading Using Deep Learning

Lu JT, Pedemonte S, Bizzo B, Doyle S, Andriole KP, Michalski MH, Gonzalez RG, Pomerantz SR.

Machine Learning Research Machine Learning for Healthcare PMLR 85:403-419, 2018

August 18, 2018

Machine Learning in Radiology: Applications beyond Image Interpretation

Lakhani P, Prater AB, Hutson RK, Andriole KP, Dreyer KJ, Morey J, Prevedello LM, Clark TJ, Geis JR, Itri JN, Hawkins CM.

J Am Coll Radiol. 2018 Feb;15(2):350-359. doi: 10.1016/j.jacr.2017.09.044. Epub 2017 Nov 17. PMID:29158061

February 15, 2018

Computed Tomography Window Blending: Feasibility in Thoracic Trauma

Mandell JC, Wortman JR, Rocha TC, Folio LR, Andriole KP, Khurana B.

Academic Radiology 25 (9), 1190-1200. 2017

February 7, 2018

Quality Improvement of Breast Magnetic Resonance Imaging Reports with Standardized Templates for Structured Reporting

Sippo DA, Birdwell, RL, Andriole KP, Raza S.

J American College of Radiology JACR 2017; 14(4):517-520

September 24, 2017

Creation of an Open Framework for Point-of-Care Computer-Assisted Reporting and Decision Support Tools for Radiologists

Almeida RR, Bizzo BC, Singh R, Andriole KP, Alkasab T.

J Am Coll Radiol. 2017 Sep;14(9):1184-1189. doi: 10.1016/j.jacr.2017.04.031.

June 23, 2017

(2017), Using clinically acquired MRI to construct age-specific ADC atlases: Quantifying spatiotemporal ADC changes from birth to 6-year old

Ou Y, Zöllei L, Retzep, K, Castro V, Bates SV, Pieper S, Andriole KP, Murphy SN, Gollub RL, Grant PE.

Hum. Brain Mapp. 2017 doi:10.1002/hbm.23573

March 31, 2017

Clinical Applications of a CT Window Blending Algorithm: RADIO (Relative Attenuation-Dependent Image Overlay)

Mandel J, Khurana B, Smith SK, Dunne R, Hyun H, Andriole KP.

Journal of Digital Imaging JDI 2017; 30(3):358-368

January 17, 2017

The Standardized Exposure Index for Digital Radiography: An Opportunity for Optimization of Radiation Dose to the Pediatric Population

Ng KH, Wong JHD, Clarke GD, Allisy-Roberts P, Williams J, Burgess AE, Bushberg JT, Seibert JA, Leidholdt EMJ, Boone JM, Dance DR, Christofides S, Maidment ADA, McLean ID, Dendy PP, Heaton B, Tan SK, Borras C, Norweck JT, Andriole KP, et al.

Problems and Solutions in Medical Physics. 2018; 16:1-7

April 14, 2011

Category: Imaging (AP, Breast, Neuro, Path, Thoracic)

Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT

Large Scale Model Validation in Healthcare

Predictive values of AI-based triage model in suboptimal CT pulmonary angiography

Development and Clinical Application of a Deep Learning Model to Identify Acute Infarct on Magnetic Resonance Imaging

A Fully Automated Deep Learning Pipeline for Multi–Vertebral Level Quantification and Characterization of Muscle and Adipose Tissue on Chest CT Scans

Lessons Learned From the Front Lines of Artificial Intelligence Implementation

Data Management in Artificial Intelligence-Assisted Radiology Reporting

The Trials and Tribulations of Assembling Large Medical Imaging Datasets for Machine Learning

The Composite Severity Score for Lumbar Spine MRI: a Metric of Cumulative Degenerative Disease Predicts Time Spent on Interpretation and Reporting

A Deep Learning-based Model for Detecting Abnormalities on Brain MRI for Triaging: Preliminary Results from a Multi-site Experience

Effects of age and sex on the distribution and symmetry of lumbar spinal and neural foraminal stenosis: a natural language processing analysis of 43,255 lumbar MRI reports

Computer-Assisted Reporting and Decision Support (CAR-DS) Increases Compliance with Follow-up Imaging and Hormonal Screening of Adrenal Incidentalomas

Population-scale CT-based body composition analysis of a large, previously healthy outpatient population using deep learning to derive age, gender and race specific reference curves

A Conference-Friendly, Hands-On Introduction to Deep Learning for Radiology Trainees

Lumbar MRI Reporting Efficiency for Trainees over the Academic Year: An Opportunity for Improving Clinical Workflows in Academic Medical Centers

Initial Experience Integrating a Hands-On Innovation Curriculum into a Radiology Residency Program and Department

An Overview and Case Study of the Clinical AI Model Development life Cycle for Healthcare Systems

Using DICOM Metadata for Radiological Image Series Categorization: A Feasibility Study on Large Clinical Brain MRI Datasets

DeepAAA: Clinically Applicable and Generalizable Detection of Abdominal Aortic Aneurysm Using Deep Learning

The RSNA Pediatric Bone Age Machine Learning Challenge

Deep Learning for Acute Ischemic Stroke on Diffusion MRI: Performance Analysis in a Consecutive Cohort

Interpretable Deep Learning-Based Characterization of Intracranial Hemorrhage on Head CT

Challenges Related to Artificial Intelligence Research in Medical Imaging and the Importance of Image Analysis Competitions

The Need for a Machine Learning Curriculum for Radiologists

Implementing the DICOM Standard for Digital Pathology

Fully Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks

Detection and Delineation of Acute Cerebral Infarct on DWI using Weakly Supervised Machine Learning

Medical Image Synthesis for Data Augmentation and Anonymization Using Generative Adversarial Networks

Deep Spine: Automated Lumbar Vertebral Segmentation, Disc-level Designation and Spinal Stenosis Grading Using Deep Learning

Machine Learning in Radiology: Applications beyond Image Interpretation

Computed Tomography Window Blending: Feasibility in Thoracic Trauma

Quality Improvement of Breast Magnetic Resonance Imaging Reports with Standardized Templates for Structured Reporting

Creation of an Open Framework for Point-of-Care Computer-Assisted Reporting and Decision Support Tools for Radiologists

(2017), Using clinically acquired MRI to construct age-specific ADC atlases: Quantifying spatiotemporal ADC changes from birth to 6-year old

Clinical Applications of a CT Window Blending Algorithm: RADIO (Relative Attenuation-Dependent Image Overlay)

The Standardized Exposure Index for Digital Radiography: An Opportunity for Optimization of Radiation Dose to the Pediatric Population