Center for Computational Imaging and Personalized Diagnostics Publications

Sunday, January 1, 2017

PD65-08 DISTINGUISHING LOW VERSUS HIGH RISK PROSTATE CANCER LESIONS USING RADIOMIC FEATURES DERIVED FROM MULTI-PARAMETRIC MAGNETIC RESONANCE IMAGING (MRI)

Shiradkar, R., Ghose, S., Villani, R., Ben-Levi, E., Rastinehad, A., & Madabhushi, A. (2017). PD65-08 DISTINGUISHING LOW VERSUS HIGH RISK PROSTATE CANCER LESIONS USING RADIOMIC FEATURES DERIVED FROM MULTI-PARAMETRIC MAGNETIC RESONANCE IMAGING (MRI). The Journal of Urology, 197 (4).

Sunday, January 1, 2017

Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images

WAng, X., Janowczyk, A., Zhou, Y., Thawani, R., Fu, P., Schalper, K., ... Madabhushi, A. (2017). Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images. Scientific Reports, 7 (1).

Sunday, January 1, 2017

Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma

Beig, N., Patel, S., Prasanna, P., Partovi, S., Varadan, V., Madabhushi, A., ... Tiwari, P. (2017). Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma. SPIE Medical Imaging, 10134 ().

Sunday, January 1, 2017

Single cell qPCR reveals that additional HAND2 and microRNA-1 facilitate the early reprogramming progress of seven-factor-induced human myocytes

Bektik, E., Dennis, A., Prasanna, P., Madabhushi, A., & Fu, J. (2017). Single cell qPCR reveals that additional HAND2 and microRNA-1 facilitate the early reprogramming progress of seven-factor-induced human myocytes. PLoS ONE, 12 (8).

Sunday, January 1, 2017

Special Section Guest Editorial: Digital Pathology

Gurcan, M., Tomaszewski, J., & Madabhushi, A. (2017). Special Section Guest Editorial: Digital Pathology. Journal of Medical Imaging, 4 (2).

Sunday, January 1, 2017

Field effect induced organ distension (FOrge) features predicting biochemical recurrence from pre-treatment prostate MRI

Ghose, S., Shiradkar, R., Rusu, M., Mitra, J., Thawani, R., Feldman, M., ... Madabhushi, A. (2017). Field effect induced organ distension (FOrge) features predicting biochemical recurrence from pre-treatment prostate MRI. , 10434 LNCS (), 442-449.

Sunday, January 1, 2017

Abstract 1080: Targeting the PI3K-Akt and NF-?B pathways as a combination therapy in blocking prostate cancer progression

Shankar, E., Kanwal, R., Goel, A., Yang, X., Shukla, S., MacLennan, G., ... Gupta, S. (2017). Abstract 1080: Targeting the PI3K-Akt and NF-?B pathways as a combination therapy in blocking prostate cancer progression. Cancer Research, 77 (13 Supplement), 1080-1080.

Sunday, January 1, 2017

An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival

Lu, C., Lewis, J., Dupont, W., Plummer, W., Janowczyk, A., & Madabhushi, A. (2017). An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival. Modern Pathology, ().

Sunday, January 1, 2017

Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features

Singanamalli, A., Wang, H., & Madabhushi, A. (2017). Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features. Scientific Reports, 7 (1).

Sunday, January 1, 2017

Changes in Computer Extracted Features of Vessel Tortuosity on CT Scans Post-Treatment in Responders Compared to Non-Responders for NonSmall Cell Lung Cancer on Immunotherapy

Velcheti, V., Alilou, M., Khunger, M., Thawani, R., & Madabhushi, A. (2017). Changes in Computer Extracted Features of Vessel Tortuosity on CT Scans Post-Treatment in Responders Compared to Non-Responders for NonSmall Cell Lung Cancer on Immunotherapy. Journal of Thoracic Oncology, 12 (8).

Sunday, January 1, 2017

Connecting Markov random fields and active contour models: application to gland segmentation and classification

Xue, Z., Monaco, J., Sparks, R., & Madabhushi, A. (2017). Connecting Markov random fields and active contour models: application to gland segmentation and classification. Journal of Medical Imaging, 4 (2).

Sunday, January 1, 2017

Co-Registration of ex vivo Surgical Histopathology and in vivo T2 weighted MRI of the Prostate via multi-scale spectral embedding representation

Li, L., Pahwa, S., Penzias, G., Rusu, M., Gollamudi, J., Viswanath, S. E., ... Madabhushi, A. (2017). Co-Registration of ex vivo Surgical Histopathology and in vivo T2 weighted MRI of the Prostate via multi-scale spectral embedding representation. Scientific Reports, 7 (1).

Sunday, January 1, 2017

MEDU-48. MRI TEXTURAL FEATURES CAN DIFFERENTIATE PEDIATRIC POSTERIOR FOSSA TUMORS

Beig, N., Correa, R., Thawani, R., Prasanna, P., Badve, C., Gold, D., ... Tiwari, P. (2017). MEDU-48. MRI TEXTURAL FEATURES CAN DIFFERENTIATE PEDIATRIC POSTERIOR FOSSA TUMORS. Neuro-Oncology, 19 (suppl_4), iv47-iv47.

Sunday, January 1, 2017

Discriminative Scale Learning (DiScrn): Applications to Prostate Cancer Detection from MRI and Needle Biopsies

Wang, H., Viswanath, S. E., & Madabhushi, A. (2017). Discriminative Scale Learning (DiScrn): Applications to Prostate Cancer Detection from MRI and Needle Biopsies. Scientific Reports, 7 (1).

Sunday, January 1, 2017

PD33-02 PROSTATE CANCER AGGRESSIVENESS IS MEDIATED BY AKT AND NF-?B SIGNALING PATHWAYS: A SYSTEMS BIOLOGY APPROACH

Shankar, E., Kanwal, R., Goel, A., Yang, X., Shukla, S., MacLennan, G., ... Gupta, S. (2017). PD33-02 PROSTATE CANCER AGGRESSIVENESS IS MEDIATED BY AKT AND NF-?B SIGNALING PATHWAYS: A SYSTEMS BIOLOGY APPROACH. The Journal of Urology, 197 (4).

Monday, December 19, 2016

Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi-institutional study.

Ginsburg, S., Algohary, A., Pahwa, S., Gulani, V., Ponsky, L., Aronen, H., ... Madabhushi, A. (2016). Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi-institutional study.. Journal of magnetic resonance imaging : JMRI, ().

Thursday, December 1, 2016

Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study.

Tiwari, P., Prasanna, P., Wolansky, L., Pinho, M., Cohen, M., Nayate, A., ... Madabhushi, A. (2016). Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study.. AJNR. American journal of neuroradiology, 37 (12), 2231-2236.

Thursday, December 1, 2016

Patient-specific pharmacokinetic parameter estimation on dynamic contrast-enhanced MRI of prostate: Preliminary evaluation of a novel AIF-free estimation method.

Ginsburg, S., Taimen, P., Merisaari, H., Vainio, P., Boström, P., Aronen, H., ... Madabhushi, A. (2016). Patient-specific pharmacokinetic parameter estimation on dynamic contrast-enhanced MRI of prostate: Preliminary evaluation of a novel AIF-free estimation method.. Journal of magnetic resonance imaging : JMRI, 44 (6), 1405-1414.

Tuesday, November 22, 2016

Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor.

Prasanna, P., Tiwari, P., & Madabhushi, A. (2016). Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor.. Scientific reports, 6 (), 37241.

Thursday, November 10, 2016

Radiomics based targeted radiotherapy planning (Rad-TRaP): A computational framework for prostate cancer treatment planning with MRI

Shiradkar, R., Podder, T., Algohary, A., Viswanath, S. E., Ellis, R., & Madabhushi, A. (2016). Radiomics based targeted radiotherapy planning (Rad-TRaP): A computational framework for prostate cancer treatment planning with MRI. Radiation Oncology, 11 (1).

Thursday, November 10, 2016

Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI.

Shiradkar, R., Podder, T., Algohary, A., Viswanath, S. E., Ellison, C., & Madabhushi, A. (2016). Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI.. Radiation oncology (London, England), 11 (1), 148.

Monday, October 24, 2016

Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings.

Prasanna, P., Patel, J., Partovi, S., Madabhushi, A., & Tiwari, P. (2016). Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings.. European radiology, ().

Monday, October 3, 2016

Multi-Pass Adaptive Voting for Nuclei Detection in Histopathological Images.

Lu, W., Xu, Y., Xu, J., Gilmore, H., Mandal, M., & Madabhushi, A. (2016). Multi-Pass Adaptive Voting for Nuclei Detection in Histopathological Images.. Scientific reports, 6 (), 33985.

Saturday, October 1, 2016

Evaluating stability of histomorphometric features across scanner and staining variations: prostate cancer diagnosis from whole slide images.

De Leon, A., Lee, G., Shih, N., Elliott, R., Feldman, M., & Madabhushi, A. (2016). Evaluating stability of histomorphometric features across scanner and staining variations: prostate cancer diagnosis from whole slide images.. Journal of medical imaging (Bellingham, Wash.), 3 (4), 047502.

Saturday, October 1, 2016

Image analysis and machine learning in digital pathology: Challenges and opportunities.

Madabhushi, A., & Lee, G. (2016). Image analysis and machine learning in digital pathology: Challenges and opportunities.. Medical image analysis, 33 (), 170-5.

Case School of Engineering

Center for Computational Imaging and Personalized Diagnostics

Center for Computational Imaging and Personalized Diagnostics Publications

PD65-08 DISTINGUISHING LOW VERSUS HIGH RISK PROSTATE CANCER LESIONS USING RADIOMIC FEATURES DERIVED FROM MULTI-PARAMETRIC MAGNETIC RESONANCE IMAGING (MRI)

Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images

Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma

Single cell qPCR reveals that additional HAND2 and microRNA-1 facilitate the early reprogramming progress of seven-factor-induced human myocytes

Special Section Guest Editorial: Digital Pathology

Field effect induced organ distension (FOrge) features predicting biochemical recurrence from pre-treatment prostate MRI

Abstract 1080: Targeting the PI3K-Akt and NF-?B pathways as a combination therapy in blocking prostate cancer progression

An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival

Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features

Changes in Computer Extracted Features of Vessel Tortuosity on CT Scans Post-Treatment in Responders Compared to Non-Responders for NonSmall Cell Lung Cancer on Immunotherapy

Connecting Markov random fields and active contour models: application to gland segmentation and classification

Co-Registration of ex vivo Surgical Histopathology and in vivo T2 weighted MRI of the Prostate via multi-scale spectral embedding representation

MEDU-48. MRI TEXTURAL FEATURES CAN DIFFERENTIATE PEDIATRIC POSTERIOR FOSSA TUMORS

Discriminative Scale Learning (DiScrn): Applications to Prostate Cancer Detection from MRI and Needle Biopsies

PD33-02 PROSTATE CANCER AGGRESSIVENESS IS MEDIATED BY AKT AND NF-?B SIGNALING PATHWAYS: A SYSTEMS BIOLOGY APPROACH

Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi-institutional study.

Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study.

Patient-specific pharmacokinetic parameter estimation on dynamic contrast-enhanced MRI of prostate: Preliminary evaluation of a novel AIF-free estimation method.

Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor.

Radiomics based targeted radiotherapy planning (Rad-TRaP): A computational framework for prostate cancer treatment planning with MRI

Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI.

Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings.

Multi-Pass Adaptive Voting for Nuclei Detection in Histopathological Images.

Evaluating stability of histomorphometric features across scanner and staining variations: prostate cancer diagnosis from whole slide images.

Image analysis and machine learning in digital pathology: Challenges and opportunities.

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