Machine learning applications in prostate cancer magnetic resonance imaging
R Cuocolo, MB Cipullo, A Stanzione, L Ugga… - European radiology …, 2019 - Springer
With this review, we aimed to provide a synopsis of recently proposed applications of
machine learning (ML) in radiology focusing on prostate magnetic resonance imaging (MRI) …
machine learning (ML) in radiology focusing on prostate magnetic resonance imaging (MRI) …
Machine learning applications in detection and diagnosis of urology cancers: a systematic literature review
Deep learning integration in cancer diagnosis enhances accuracy and diagnosis speed
which helps clinical decision-making and improves health outcomes. Despite all these …
which helps clinical decision-making and improves health outcomes. Despite all these …
Classification of cancer at prostate MRI: deep learning versus clinical PI-RADS assessment
Background Men suspected of having clinically significant prostate cancer (sPC)
increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic …
increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic …
Deep‐learning models for detection and localization of visible clinically significant prostate cancer on multi‐parametric MRI
Z Sun, P Wu, Y Cui, X Liu, K Wang… - Journal of Magnetic …, 2023 - Wiley Online Library
Background Deep learning for diagnosing clinically significant prostate cancer (csPCa) is
feasible but needs further evaluation in patients with prostate‐specific antigen (PSA) levels …
feasible but needs further evaluation in patients with prostate‐specific antigen (PSA) levels …
Recent automatic segmentation algorithms of MRI prostate regions: a review
World-wide incidence rate of prostate cancer has progressively increased with time
especially with the increased proportion of elderly population. Early detection of prostate …
especially with the increased proportion of elderly population. Early detection of prostate …
Automatic segmentation of pelvic cancers using deep learning: State-of-the-art approaches and challenges
R Kalantar, G Lin, JM Winfield, C Messiou… - Diagnostics, 2021 - mdpi.com
The recent rise of deep learning (DL) and its promising capabilities in capturing non-explicit
detail from large datasets have attracted substantial research attention in the field of medical …
detail from large datasets have attracted substantial research attention in the field of medical …
A convolutional neural network-based system to classify patients using FDG PET/CT examinations
Background As the number of PET/CT scanners increases and FDG PET/CT becomes a
common imaging modality for oncology, the demands for automated detection systems on …
common imaging modality for oncology, the demands for automated detection systems on …
H-ProSeg: Hybrid ultrasound prostate segmentation based on explainability-guided mathematical model
Abstract Background and Objective Accurate and robust prostate segmentation in transrectal
ultrasound (TRUS) images is of great interest for image-guided prostate interventions and …
ultrasound (TRUS) images is of great interest for image-guided prostate interventions and …
Anisotropic 3D multi-stream CNN for accurate prostate segmentation from multi-planar MRI
Abstract Background and Objective: Accurate and reliable segmentation of the prostate
gland in MR images can support the clinical assessment of prostate cancer, as well as the …
gland in MR images can support the clinical assessment of prostate cancer, as well as the …
Deep learning in radiation oncology treatment planning for prostate cancer: a systematic review
G Almeida, JMRS Tavares - Journal of medical systems, 2020 - Springer
Radiation oncology for prostate cancer is important as it can decrease the morbidity and
mortality associated with this disease. Planning for this modality of treatment is both …
mortality associated with this disease. Planning for this modality of treatment is both …