Harri Merisaari

Publications

Leo, P., Janowczyk, A., Elliott, R., Janaki, N., Bera, K., Shiradkar, R., Farre, X., Fu, P., El-Fahmawi, A., Shahait, M., Kim, J., Lee, D., Yamoah, K., Rebbeck, T., Khani, F., Robinson, B., Eklund, L., Jambor, I., Merisaari, H., , O., Taimen, P., Aronen, H., Boström, P., Tewari, A., Magi-Galluzzi, C., Klein, E., Purysko, A., Shin, N., Feldman, M., Gupta, S., Lai, P., & Madabhushi, A. (2021). Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study. NPJ Precision Oncology, 5 (1), 35.
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.
Hiremath, A., Shiradkar, R., Merisaari, H., Li, L., Prasanna, P., Ettala, O., Taimen, P., Aronen, H., Boström, P., Pierce, J., Tirumani, S., Rastinehad, A., Jambor, I., Purysko, A., & Madabhushi, A. (2020). PD57-05 A DEEP LEARNING NETWORK ALONG WITH PIRADS CAN DISTINGUISH CLINICALLY SIGNIFICANT AND INSIGNIFICANT PROSTATE CANCER ON BI-PARAMETRIC MRI: A MULTI-CENTER STUDY. The Journal of Urology, 203
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.
Li, L., Jambor, I., Taimen, P., Merisaari, H., Minn, H., Boström, P., Aronen, H., Algohary, A., & Madabhushi, A. (2018). MP35-01 PROSTATE TUMOR TEXTURAL HETEROGENEITY OF 11 C-ACETATE POSITRON EMISSION TOMOGRAPHY AND T2-WEIGHTED MAGNETIC RESONANCE IMAGING CORRELATE WITH BIOCHEMICAL RECURRENCE: PRELIMINARY FINDINGS. The Journal of Urology, 199 (4).
Ginsburg, S., Taimen, P., Merisaari, H., Vainio, P., Boström, P., Aronen, H., Jambor, I., & 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.
Ginsburg, S., Taimen, P., Merisaari, H., Vainio, P., Boström, P., Aronen, H., Jambor, I., & Madabhushi, A. (2016). Patient-specific pharmacokinetic parameter estimation on dynamic contrast-enhanced MRI of prostate: Preliminary evaluation of a novel AIF-free estimation method: AIF-Free Pharmacokinetic Parameter Estimation. Journal of Magnetic Resonance Imaging [10531807], 44 (6), 1405-1414.