Search results for "lesion detection"
showing 3 items of 3 documents
Prospective Image Quality and Lesion Assessment in the Setting of MR-Guided Radiation Therapy of Prostate Cancer on an MR-Linac at 1.5 T: A Compariso…
2021
The objective of this study is to conduct a qualitative and a quantitative image quality and lesion evaluation in patients undergoing MR-guided radiation therapy (MRgRT) for prostate cancer on a hybrid magnetic resonance imaging and linear accelerator system (MR-Linac or MRL) at 1.5 Tesla. This prospective study was approved by the institutional review board. A total of 13 consecutive patients with biopsy-confirmed prostate cancer and an indication for MRgRT were included. Prior to radiation therapy, each patient underwent an MR-examination on an MRL and on a standard MRI scanner at 3 Tesla (MRI3T). Three readers (two radiologists and a radiation oncologist) conducted an independent qualita…
Dual-Time Point [68Ga]Ga-PSMA-11 PET/CT Hybrid Imaging for Staging and Restaging of Prostate Cancer
2020
Routine [68Ga]Ga-PSMA-11 PET/CT (one hour post-injection) has been shown to accurately detect prostate cancer (PCa) lesions. The goal of this study is to evaluate the benefit of a dual-time point imaging modality for the staging and restaging of PCa patients. Biphasic [68Ga]Ga-PSMA-11 PET/CT of 233 patients, who underwent early and late scans (one/three hours post-injection), were retrospectively studied. Tumor uptake and biphasic lesion detection for 215 biochemically recurrent patients previously treated for localized PCa (prostatectomized patients (P-P)/irradiated patients (P-I) and 18 patients suspected of having primary PCa (P-T) were separately evaluated. Late [68Ga]Ga-PSMA-11 PET/CT …
Semi-automated and interactive segmentation of contrast-enhancing masses on breast DCE-MRI using spatial fuzzy clustering
2022
Abstract Multiparametric Magnetic Resonance Imaging (MRI) is the most sensitive imaging modality for breast cancer detection and is increasingly playing a key role in lesion characterization. In this context, accurate and reliable quantification of the shape and extent of breast cancer is crucial in clinical research environments. Since conventional lesion delineation procedures are still mostly manual, automated segmentation approaches can improve this time-consuming and operator-dependent task by annotating the regions of interest in a reproducible manner. In this work, a semi-automated and interactive approach based on the spatial Fuzzy C-Means (sFCM) algorithm is proposed, used to segme…