Search Results - Shiradkar, Rakesh

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  1. 1
    Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review

    Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review by Lu, Cheng, Shiradkar, Rakesh, Liu, Zaiyi

    Published 2021
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  2. 2
    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 by Shiradkar, Rakesh, Podder, Tarun K, Algohary, Ahmad, Viswanath, Satish, Ellis, Rodney J., Madabhushi, Anant

    Published 2016
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  3. 3
    Radiomic Features from Pretreatment Biparametric Magnetic Resonance Imaging Predict Prostate Cancer Biochemical Recurrence: Preliminary Findings

    Radiomic Features from Pretreatment Biparametric Magnetic Resonance Imaging Predict Prostate Cancer Biochemical Recurrence: Preliminary Findings by Shiradkar, Rakesh, Ghose, Soumya, Jambor, Ivan, Taimen, Pekka, Ettala, Otto, Purysko, Andrei S, Madabhushi, Anant

    Published 2018
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  4. 4
    Prostate shapes on pre-treatment MRI between prostate cancer patients who do and do not undergo biochemical recurrence are different: Preliminary Findings

    Prostate shapes on pre-treatment MRI between prostate cancer patients who do and do not undergo biochemical recurrence are different: Preliminary Findings by Ghose, Soumya, Shiradkar, Rakesh, Rusu, Mirabela, Mitra, Jhimli, Thawani, Rajat, Feldman, Michael, Gupta, Amar C., Purysko, Andrei S., Ponsky, Lee, Madabhushi, Anant

    Published 2017
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  5. 5
    Prostate Surface Distension and Tumor Texture Descriptors From Pre-Treatment MRI Are Associated With Biochemical Recurrence Following Radical Prostatectomy: Preliminary Findings

    Prostate Surface Distension and Tumor Texture Descriptors From Pre-Treatment MRI Are Associated With Biochemical Recurrence Following Radical Prostatectomy: Preliminary Findings by Shiradkar, Rakesh, Ghose, Soumya, Mahran, Amr, Li, Lin, Hubbard, Isaac, Fu, Pingfu, Tirumani, Sree Harsha, Ponsky, Lee, Purysko, Andrei, Madabhushi, Anant

    Published 2022
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  6. 6
    Repeatability of radiomics and machine learning for Diffusion Weighted Imaging: Short-term repeatability study of 112 patients with prostate cancer

    Repeatability of radiomics and machine learning for Diffusion Weighted Imaging: Short-term repeatability study of 112 patients with prostate cancer by Merisaari, Harri, Taimen, Pekka, Shiradkar, Rakesh, Ettala, Otto, Pesola, Marko, Saunavaara, Jani, Boström, Peter J., Madabhushi, Anant, Aronen, Hannu J., Jambor, Ivan

    Published 2019
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  7. 7
    Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps

    Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps by Hiremath, Amogh, Shiradkar, Rakesh, Merisaari, Harri, Prasanna, Prateek, Ettala, Otto, Taimen, Pekka, Aronen, Hannu J., Boström, Peter J., Jambor, Ivan, Madabhushi, Anant

    Published 2020
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  8. 8
    An integrated nomogram combining deep learning, Prostate Imaging–Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant prostate cancer on biparametric MRI: a retrospective multicentre study

    An integrated nomogram combining deep learning, Prostate Imaging–Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant pr... by Hiremath, Amogh, Shiradkar, Rakesh, Fu, Pingfu, Mahran, Amr, Rastinehad, Ardeshir R, Tewari, Ashutosh, Tirumani, Sree Harsha, Purysko, Andrei, Ponsky, Lee, Madabhushi, Anant

    Published 2021
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  9. 9
    T1, T2 MR Fingerprinting Measurements of Prostate Cancer and Prostatitis Correlate with Deep Learning Derived Estimates of Epithelium, Lumen and Stromal Composition on Corresponding Whole Mount Histopathology

    T1, T2 MR Fingerprinting Measurements of Prostate Cancer and Prostatitis Correlate with Deep Learning Derived Estimates of Epithelium, Lumen and Stromal Composition on Correspondin... by Shiradkar, Rakesh, Panda, Ananya, Leo, Patrick, Janowczyk, Andrew, Farre, Xavier, Janaki, Nafiseh, Li, Lin, Pahwa, Shivani, Mahran, Amr, Buzzy, Christina, Fu, Ping, Elliott, Robin, MacLennan, Gregory, Ponsky, Lee, Gulani, Vikas, Madabhushi, Anant

    Published 2020
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  10. 10
    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 by Algohary, Ahmad, Shiradkar, Rakesh, Pahwa, Shivani, Purysko, Andrei, Verma, Sadhna, Moses, Daniel, Shnier, Ronald, Haynes, Anne-Maree, Delprado, Warick, Thompson, James, Tirumani, Sreeharsha, Mahran, Amr, Rastinehad, Ardeshir R, Ponsky, Lee, Stricker, Phillip D., Madabhushi, Anant

    Published 2020
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  11. 11
    Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary Findings

    Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary Findings by Algohary, Ahmad, Viswanath, Satish, Shiradkar, Rakesh, Ghose, Soumya, Pahwa, Shivani, Moses, Daniel, Jambor, Ivan, Shnier, Ronald, Böhm, Maret, Haynes, Anne-Maree, Brenner, Phillip, Delprado, Warick, Thompson, James, Pulbrock, Marley, Purysko, Andrei, Verma, Sadhna, Ponsky, Lee, Stricker, Phillip, Madabhushi, Anant

    Published 2018
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  12. 12
    A novel imaging based Nomogram for predicting post-surgical biochemical recurrence and adverse pathology of prostate cancer from pre-operative bi-parametric MRI

    A novel imaging based Nomogram for predicting post-surgical biochemical recurrence and adverse pathology of prostate cancer from pre-operative bi-parametric MRI by Li, Lin, Shiradkar, Rakesh, Leo, Patrick, Algohary, Ahmad, Fu, Pingfu, Tirumani, Sree Harsha, Mahran, Amr, Buzzy, Christina, Obmann, Verena C, Mansoori, Bahar, El-Fahmawi, Ayah, Shahait, Mohammed, Tewari, Ashutosh, Magi-Galluzzi, Cristina, Lee, David, Lal, Priti, Ponsky, Lee, Klein, Eric, Purysko, Andrei S., Madabhushi, Anant

    Published 2020
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  13. 13
    Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study

    Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study by Leo, Patrick, Janowczyk, Andrew, Elliott, Robin, Janaki, Nafiseh, Bera, Kaustav, Shiradkar, Rakesh, Farré, Xavier, Fu, Pingfu, El-Fahmawi, Ayah, Shahait, Mohammed, Kim, Jessica, Lee, David, Yamoah, Kosj, Rebbeck, Timothy R., Khani, Francesca, Robinson, Brian D., Eklund, Lauri, Jambor, Ivan, Merisaari, Harri, Ettala, Otto, Taimen, Pekka, Aronen, Hannu J., Boström, Peter J., Tewari, Ashutosh, Magi-Galluzzi, Cristina, Klein, Eric, Purysko, Andrei, NC Shih, Natalie, Feldman, Michael, Gupta, Sanjay, Lal, Priti, Madabhushi, Anant

    Published 2021
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