Computer-aided detection of prostate cancer with MRI: technology and applications
One in six men will develop prostate cancer in his lifetime. Early detection and accurate
diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently …
diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently …
Novel quantitative imaging for predicting response to therapy: techniques and clinical applications
The current standard of Response Evaluation Criteria in Solid Tumors (RECIST)–based
tumor response evaluation is limited in its ability to accurately monitor treatment response …
tumor response evaluation is limited in its ability to accurately monitor treatment response …
Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization
Purpose To develop and validate a classifier system for prediction of prostate cancer (PCa)
Gleason score (GS) using radiomics and texture features of T2-weighted imaging (T2w) …
Gleason score (GS) using radiomics and texture features of T2-weighted imaging (T2w) …
Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: preliminary findings
Background Radiomics or computer‐extracted texture features derived from MRI have been
shown to help quantitatively characterize prostate cancer (PCa). Radiomics have not been …
shown to help quantitatively characterize prostate cancer (PCa). Radiomics have not been …
Combination of peri-tumoral and intra-tumoral radiomic features on bi-parametric MRI accurately stratifies prostate cancer risk: a multi-site study
Background: Prostate cancer (PCa) influences its surrounding habitat, which tends to
manifest as different phenotypic appearances on magnetic resonance imaging (MRI). This …
manifest as different phenotypic appearances on magnetic resonance imaging (MRI). This …
Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: preliminary findings from a multi‐institutional study
SB Ginsburg, A Algohary, S Pahwa… - Journal of Magnetic …, 2017 - Wiley Online Library
Purpose To evaluate in a multi‐institutional study whether radiomic features useful for
prostate cancer (PCa) detection from 3 Tesla (T) multi‐parametric MRI (mpMRI) in the …
prostate cancer (PCa) detection from 3 Tesla (T) multi‐parametric MRI (mpMRI) in the …
Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary findings
Background Radiomic analysis is defined as computationally extracting features from
radiographic images for quantitatively characterizing disease patterns. There has been …
radiographic images for quantitatively characterizing disease patterns. There has been …
Clinically significant prostate cancer detection on MRI: A radiomic shape features study
Abstract Purpose Prostate multiparametric MRI (mpMRI) is the imaging modality of choice for
detecting clinically significant prostate cancer (csPCa). Among various parameters, lesion …
detecting clinically significant prostate cancer (csPCa). Among various parameters, lesion …
Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer
Background Gene-expression companion diagnostic tests, such as the Oncotype DX test,
assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide …
assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide …
Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI
Background Radiomics or computer–extracted texture features have been shown to achieve
superior performance than multiparametric MRI (mpMRI) signal intensities alone in targeting …
superior performance than multiparametric MRI (mpMRI) signal intensities alone in targeting …