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We investigate the connection between visual semantic features defined in PI-RADS and associated risk factors, moving beyond abnormal imaging findings, establishing a shared framework between medical and AI professionals by creating a…

Prostate cancer (Pca) continues to be a leading cause of cancer-related mortality in men, and the limitations in precision of traditional diagnostic methods such as the Digital Rectal Exam (DRE), Prostate-Specific Antigen (PSA) testing, and…

Multi-parametric magnetic resonance imaging (mpMRI) has a growing role in detecting prostate cancer lesions. Thus, it is pertinent that medical professionals who interpret these scans reduce the risk of human error by using computer-aided…

Image and Video Processing · Electrical Eng. & Systems 2022-08-25 Haoli Yin , Nithin Buduma

Deep learning models have had a great success in disease classifications using large data pools of skin cancer images or lung X-rays. However, data scarcity has been the roadblock of applying deep learning models directly on prostate…

Computer Vision and Pattern Recognition · Computer Science 2021-01-27 Weiwei Zong , Joon Lee , Chang Liu , Eric Carver , Aharon Feldman , Branislava Janic , Mohamed Elshaikh , Milan Pantelic , David Hearshen , Indrin Chetty , Benjamin Movsas , Ning Wen

Recent advances in medical imaging techniques have led to significant improvements in the management of prostate cancer (PCa). In particular, multi-parametric MRI (mp-MRI) continues to gain clinical acceptance as the preferred imaging…

Image and Video Processing · Electrical Eng. & Systems 2019-10-08 Ruiming Cao , Xinran Zhong , Fabien Scalzo , Steven Raman , Kyung hyun Sung

Prostate cancer, the second most prevalent male malignancy, requires advanced diagnostic tools. We propose an explainable AI system combining BERT (for textual clinical notes) and Random Forest (for numerical lab data) through a novel…

Prostate cancer is the second deadliest cancer for American men. While Magnetic Resonance Imaging (MRI) is increasingly used to guide targeted biopsies for prostate cancer diagnosis, its utility remains limited due to high rates of false…

Prostate cancer (PCa) is the most frequently diagnosed malignancy in men and the eighth leading cause of cancer death worldwide. Multiparametric MRI (mpMRI) has become central to the diagnostic pathway for men at intermediate risk,…

PURPOSE: Deep learning methods for classifying prostate cancer (PCa) in ultrasound images typically employ convolutional networks (CNNs) to detect cancer in small regions of interest (ROI) along a needle trace region. However, this approach…

Prostate cancer is the most dangerous cancer diagnosed in men worldwide. Prostate diagnosis has been affected by many factors, such as lesion complexity, observer visibility, and variability. Many techniques based on Magnetic Resonance…

Image and Video Processing · Electrical Eng. & Systems 2022-08-02 Hussein Hashem , Yasmin Alsakar , Ahmed Elgarayhi , Mohammed Elmogy , Mohammed Sallah

The diagnosis of prostate cancer is challenging due to the heterogeneity of its presentations, leading to the over diagnosis and treatment of non-clinically important disease. Accurate diagnosis can directly benefit a patient's quality of…

Prostate cancer is a commonly diagnosed cancerous disease among men world-wide. Even with modern technology such as multi-parametric magnetic resonance tomography and guided biopsies, the process for diagnosing prostate cancer remains time…

Image and Video Processing · Electrical Eng. & Systems 2024-04-17 Malte Rippa , Ruben Schulze , Marian Himstedt , Felice Burn

Prostate cancer is among the most common cancer in males and its heterogeneity is well known. Its early detection helps making therapeutic decision. There is no standard technique or procedure yet which is full-proof in predicting cancer…

Machine Learning · Computer Science 2018-12-18 Khalid Raza , Atif N Hasan

We present a fully automated, anatomically guided deep learning pipeline for prostate cancer (PCa) risk stratification using routine MRI. The pipeline integrates three key components: an nnU-Net module for segmenting the prostate gland and…

Breast cancer is a health problem that affects mainly the female population. An early detection increases the chances of effective treatment, improving the prognosis of the disease. In this regard, computational tools have been proposed to…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Steve Tsham Mpinda Ataky , Alessandro Lameiras Koerich

In the United States, prostate cancer is the second leading cause of deaths in males with a predicted 35,250 deaths in 2024. However, most diagnoses are non-lethal and deemed clinically insignificant which means that the patient will likely…

Machine Learning · Computer Science 2024-11-08 Benjamin Ng , Chi-en Amy Tai , E. Zhixuan Zeng , Alexander Wong

Prostate cancer (PCa) is one of the leading causes of death for men worldwide. Multi-parametric magnetic resonance (mpMR) imaging has emerged as a non-invasive diagnostic tool for detecting and localising prostate tumours by specialised…

Image and Video Processing · Electrical Eng. & Systems 2021-06-07 Zhe Min , Fernando J. Bianco , Qianye Yang , Rachael Rodell , Wen Yan , Dean Barratt , Yipeng Hu

Early detection of many life-threatening diseases (e.g., prostate and breast cancer) within at-risk population can improve clinical outcomes and reduce cost of care. While numerous disease-specific "screening" tests that are closer to…

The emergence of multi-parametric magnetic resonance imaging (mpMRI) has had a profound impact on the diagnosis of prostate cancers (PCa), which is the most prevalent malignancy in males in the western world, enabling a better selection of…

While current research has shown the importance of Multi-parametric MRI (mpMRI) in diagnosing prostate cancer (PCa), further investigation is needed for how to incorporate the specific structures of the mpMRI data, such as the regional…

Machine Learning · Statistics 2021-11-04 Jin Jin , Lin Zhang , Ethan Leng , Gregory J. Metzger , Joseph S. Koopmeiners
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