Center for Computational Imaging and Personalized Diagnostics Publications

Friday, January 1, 2021

Development and evaluation of deep learningbased segmentation of histologic structures in the kidney cortex with multiple histologic stains

Jayapandian, C., Chen, Y., Janowczyk, A., Palmer, M., Cassol, C., Sekulic, M., ... Adler, S. (2021). Development and evaluation of deep learningbased segmentation of histologic structures in the kidney cortex with multiple histologic stains. Kidney International, 99 (1), 86-101.

Friday, January 1, 2021

A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer

WAng, X., Bera, K., Barrera, C., Zhou, Y., Lu, C., Vaidya, P., ... Madabhushi, A. (2021). A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer. EBIOMEDICINE, 69 ().

Friday, January 1, 2021

Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps

Hiremath, A., Shiradkar, R., Merisaari, H., Prasanna, P., Ettala, O., Taimen, P., ... Madabhushi, A. (2021). Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps. European Radiology, 31 (1), 379-391.

Tuesday, December 1, 2020

Technical Note: MRQy — An open-source tool for quality control of MR imaging data

Sadri, A., Janowczyk, A., Zhou, R., Verma, R., Beig, N., Antunes, J., ... Viswanath, S. E. (2020). Technical Note: MRQy — An open-source tool for quality control of MR imaging data. Medical Physics, 47 (12), 6029-6038.

Tuesday, December 1, 2020

Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma?-A Feasibility Study

Ismail, M., Hill, V., Statsevych, V., Mason, E., Correa, R., Prasanna, P., ... Tiwari, P. (2020). Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma?-A Feasibility Study. Frontiers in Computational Neuroscience, 14 (), 563439.

Tuesday, December 1, 2020

CT-Radiomic Approach to Predict G1/2 Nonfunctional Pancreatic Neuroendocrine Tumor

Zhao, Z., Bian, Y., Jiang, H., Fang, X., Liu, H., Cao, K., ... Lu, J. (2020). CT-Radiomic Approach to Predict G1/2 Nonfunctional Pancreatic Neuroendocrine Tumor. Academic Radiology, 27 (12), e272-e281.

Sunday, November 1, 2020

Impact of Insurance and Socioeconomic Status on HPV-related Oropharyngeal Cancer

Yang, K., Fleming, C., Contreras, G., Woody, N., Joshi, N., Geiger, J., ... Koyfman, S. (2020). Impact of Insurance and Socioeconomic Status on HPV-related Oropharyngeal Cancer. International Journal of Radiation Oncology Biology Physics, 108 (3).

Sunday, November 1, 2020

Technical Note: MRQy - An open-source tool for quality control of MR imaging data

Sadri, A., Janowczyk, A., Zhou, R., Verma, R., Beig, N., Antunes, J., ... Viswanath, S. E. (2020). Technical Note: MRQy - An open-source tool for quality control of MR imaging data. Medical Physics, 47 (12), 6029-6038.
DOI: 10.1002/mp.14593

Sunday, November 1, 2020

Radiomic Features of Primary Rectal Cancers on Baseline T 2 -Weighted MRI Are Associated With Pathologic Complete Response to Neoadjuvant Chemoradiation: A Multisite Study

Antunes, J., Ofshteyn, A., Bera, K., Wang, E., Brady, J., Willis, J., ... Viswanath, S. (2020). Radiomic Features of Primary Rectal Cancers on Baseline T 2 -Weighted MRI Are Associated With Pathologic Complete Response to Neoadjuvant Chemoradiation: A Multisite Study. Journal of Magnetic Resonance Imaging, 52 (5), 1531-1541.

Sunday, November 1, 2020

Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology

Bera, K., Katz, I., & Madabhushi, A. (2020). Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology. JCO clinical cancer informatics, 4 (), 1039-1050.

Sunday, November 1, 2020

A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study

Lu, C., Bera, K., WAng, X., Prasanna, P., Xue, Z., Janowczyk, A., ... Madabhushi, A. (2020). A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study. The Lancet Digital Health, 2 (11), e594-e606.

Sunday, November 1, 2020

A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study

Sunday, November 1, 2020

Digital pathology and computational image analysis in nephropathology

Barisoni, L., Lafata, K., Hewitt, S., Madabhushi, A., & Balis, U. (2020). Digital pathology and computational image analysis in nephropathology. Nature Reviews Nephrology, 16 (11), 669-685.

Saturday, October 17, 2020

Sexually dimorphic radiogenomic models identify distinct imaging and biological pathways that are prognostic of overall survival in Glioblastoma

Beig, N., Singh, S., Bera, K., Prasanna, P., Singh, G., Chen, J., ... Tiwari, P. (2020). Sexually dimorphic radiogenomic models identify distinct imaging and biological pathways that are prognostic of overall survival in Glioblastoma. Neuro-Oncology, ().

Thursday, October 1, 2020

Automated gleason grading on prostate biopsy slides by statistical representations of homology profile

Yan, C., Nakane, K., WAng, X., Fu, Y., Lu, H., Fan, X., ... Xue, Z. (2020). Automated gleason grading on prostate biopsy slides by statistical representations of homology profile. Computer Methods and Programs in Biomedicine, 194 ().

Thursday, October 1, 2020

Computerized Spermatogenesis Staging (CSS) of Mouse Testis Sections via Quantitative Histomorphological Analysis

Xue, Z., Lu, H., Li, H., Yan, C., WAng, X., Zang, M., ... Xu, E. (2020). Computerized Spermatogenesis Staging (CSS) of Mouse Testis Sections via Quantitative Histomorphological Analysis. Medical Image Analysis, ().

Monday, September 21, 2020

Computer Extracted Features from Initial H&E Tissue Biopsies Predict Disease Progression for Prostate Cancer Patients on Active Surveillance

Chandramouli, S., Leo, P., Lee, G., Elliott, R., Davis, C., Zhu, G., ... Madabhushi, A. (2020). Computer Extracted Features from Initial H&E Tissue Biopsies Predict Disease Progression for Prostate Cancer Patients on Active Surveillance. Cancers, 12 (9).

Friday, September 18, 2020

Correction to: T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learningderived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology

Shiradkar, R., Panda, A., Leo, P., Janowczyk, A., Farre, X., Janaki, N., ... Madabhushi, A. (2020). Correction to: T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learningderived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology. European Radiology, ().

Wednesday, September 2, 2020

T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learningderived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology

Shiradkar, R., Panda, A., Leo, P., Janowczyk, A., Farre, X., Janaki, N., ... Madabhushi, A. (2020). T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learningderived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology. European Radiology, ().

Tuesday, September 1, 2020

Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis

Chen, Y., Janowczyk, A., & Madabhushi, A. (2020). Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis. JCO Clinical Cancer Informatics, (4), 221-233.

Thursday, August 6, 2020

Combination of Peri-Tumoral and Intra-Tumoral Radiomic Features on Bi-Parametric MRI Accurately Stratifies Prostate Cancer Risk: A Multi-Site Study

Algohary, A., Shiradkar, R., Pahwa, S., Purysko, A., Verma, S., Moses, D., ... Madabhushi, A. (2020). Combination of Peri-Tumoral and Intra-Tumoral Radiomic Features on Bi-Parametric MRI Accurately Stratifies Prostate Cancer Risk: A Multi-Site Study. Cancers, 12 (8).

Saturday, August 1, 2020

Combination of peri-tumoral and intra-tumoral radiomic features on bi-parametric mri accurately stratifies prostate cancer risk: A multi-site study

Algohary, A., Shiradkar, R., Pahwa, S., Purysko, A., Verma, S., Moses, D., ... Madabhushi, A. (2020). Combination of peri-tumoral and intra-tumoral radiomic features on bi-parametric mri accurately stratifies prostate cancer risk: A multi-site study. Cancers, 12 (8), 1-14.

Saturday, August 1, 2020

Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology

Feeny, A., Chung, M., Madabhushi, A., Attia, Z., Cikes, M., Firouznia, M., ... Wang, P. (2020). Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology. Circulation - Arrhythmia and Electrophysiology, 13 (8).

Friday, July 24, 2020

Radiomic Texture and Shape Descriptors of the Rectal Environment on Post-Chemoradiation T2-Weighted MRI are Associated with Pathologic Tumor Stage Regression in Rectal Cancers: A Retrospective, Multi-Institution Study

Alvarez-Jimenez, C., Antunes, J., Talasila, N., Bera, K., Brady, J., Gollamudi, J., ... Viswanath, S. (2020). Radiomic Texture and Shape Descriptors of the Rectal Environment on Post-Chemoradiation T2-Weighted MRI are Associated with Pathologic Tumor Stage Regression in Rectal Cancers: A Retrospective, Multi-Institution Study. Cancers, 12 (8).

Wednesday, July 1, 2020

Machine Learning of 12-lead QRS Waveforms to Identify Cardiac Resynchronization Therapy Patients with Differential Outcomes

Feeny, A., Rickard, J., Trulock, K., Patel, D., Toro, S., Moennich, L., ... Chung, M. (2020). Machine Learning of 12-lead QRS Waveforms to Identify Cardiac Resynchronization Therapy Patients with Differential Outcomes. Circulation - Arrhythmia and Electrophysiology, 13 (7).

Case School of Engineering

Center for Computational Imaging and Personalized Diagnostics

Center for Computational Imaging and Personalized Diagnostics Publications

Development and evaluation of deep learningbased segmentation of histologic structures in the kidney cortex with multiple histologic stains

A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer

Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps

Technical Note: MRQy — An open-source tool for quality control of MR imaging data

Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma?-A Feasibility Study

CT-Radiomic Approach to Predict G1/2 Nonfunctional Pancreatic Neuroendocrine Tumor

Impact of Insurance and Socioeconomic Status on HPV-related Oropharyngeal Cancer

Technical Note: MRQy - An open-source tool for quality control of MR imaging data

Radiomic Features of Primary Rectal Cancers on Baseline T 2 -Weighted MRI Are Associated With Pathologic Complete Response to Neoadjuvant Chemoradiation: A Multisite Study

Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology

A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study

A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study

Digital pathology and computational image analysis in nephropathology

Sexually dimorphic radiogenomic models identify distinct imaging and biological pathways that are prognostic of overall survival in Glioblastoma

Automated gleason grading on prostate biopsy slides by statistical representations of homology profile

Computerized Spermatogenesis Staging (CSS) of Mouse Testis Sections via Quantitative Histomorphological Analysis

Computer Extracted Features from Initial H&E Tissue Biopsies Predict Disease Progression for Prostate Cancer Patients on Active Surveillance

Correction to: T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learningderived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology

T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learningderived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology

Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis

Combination of Peri-Tumoral and Intra-Tumoral Radiomic Features on Bi-Parametric MRI Accurately Stratifies Prostate Cancer Risk: A Multi-Site Study

Combination of peri-tumoral and intra-tumoral radiomic features on bi-parametric mri accurately stratifies prostate cancer risk: A multi-site study

Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology

Radiomic Texture and Shape Descriptors of the Rectal Environment on Post-Chemoradiation T2-Weighted MRI are Associated with Pathologic Tumor Stage Regression in Rectal Cancers: A Retrospective, Multi-Institution Study

Machine Learning of 12-lead QRS Waveforms to Identify Cardiac Resynchronization Therapy Patients with Differential Outcomes

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