Andrei S. Purysko
According to our database1,
Andrei S. Purysko
authored at least 10 papers
between 2017 and 2023.
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Bibliography
2023
Integrating multi-plane and multi-region radiomic features to predict pathologic response to neoadjuvant chemoradiation in rectal cancers via pre-treatment MRI.
Proceedings of the Medical Imaging 2023: Image-Guided Procedures, 2023
2022
Deep hybrid convolutional wavelet networks: application to predicting response to chemoradiation in rectal cancers via MRI.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022
Evaluating the sensitivity of deep learning to inter-reader variations in lesion delineations on bi-parametric MRI in identifying clinically significant prostate cancer.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022
2020
Multi-site evaluation of stable radiomic features for more accurate evaluation of pathologic downstaging on MRI after chemoradiation for rectal cancers.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
2019
Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-site study.
BMC Medical Imaging, 2019
Radiomic characterization of perirectal fat on MRI enables accurate assessment of tumor regression and lymph node metastasis in rectal cancers after chemoradiation.
Proceedings of the Medical Imaging 2019: Image-Guided Procedures, 2019
Radiomic features derived from pre-operative multi-parametric MRI of prostate cancer are associated with Decipher risk score.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
2018
Empirical evaluation of cross-site reproducibility in radiomic features for characterizing prostate MRI.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
2017
Field Effect Induced Organ Distension (FOrge) Features Predicting Biochemical Recurrence from Pre-treatment Prostate MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017