Otto Ettala

Publications

Hiremath, A., Shiradkar, R., Merisaari, H., Prasanna, P., Ettala, O., Taimen, P., Aronen, H., Boström, P., Jambor, I., & 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.
Hiremath, A., Shiradkar, R., Merisaari, H., Prasanna, P., Ettala, O., Taimen, P., Aronen, H., Boström, P., Jambor, I., & 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.
Merisaari, H., Taimen, P., Shiradkar, R., Ettala, O., Pesola, M., Saunavaara, J., Boström, P., Madabhushi, A., Aronen, H., & Jambor, I. (2020). Repeatability of radiomics and machine learning for DWI: Short-term repeatability study of 112 patients with prostate cancer. Magnetic Resonance in Medicine, 83 (6), 2293-2309.
Merisaari, H., Taimen, P., Shiradkar, R., Ettala, O., Persola, M., Saunavaara, J., Bostrom, P., Madabhushi, A., Aronen, H., & Jambor, I. (2019). Repeatability of radiomics and machine learning for DWI: Short-term repeatability study of 112 patients with prostate cancer. Magnetic Resonance in Imaging, 83 (6), 2293 - 2309.
Leo, P., Janowczyk, A., Elliott, R., Janaki, N., Shiradkar, R., Farr�, X., Yamoah, K., Rebbeck, T., Shih, N., Khani, F., Robinson, B., Eklund, L., Ettala, O., Taimen, P., Boström, P., Feldman, M., Gupta, S., Lal, P., & Madabhushi, A. (2019). Computerized histomorphometric features of glandular architecture predict risk of biochemical recurrence following radical prostatectomy: A multisite study.. Journal of Clinical Oncology, 37 (15_suppl), 5060-5060.
Shiradkar, R., Ghose, S., Jambor, I., Taimen, P., Ettala, O., Purysko, A., & Madabhushi, A. (2018). Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings. Journal of Magnetic Resonance Imaging, 48 (6), 1626-1636.
Shiradkar, R., Ghose, S., Jambor, I., Taimen, P., Ettala, O., Purysko, A., & Madabhushi, A. (2018). Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings: Prostate Cancer Recurrence Prediction. Journal of Magnetic Resonance Imaging.