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Accurate segmentation of the prostate gland in multiparametric MRI (mpMRI) is a fundamental step for a wide range of clinical and research applications, including image registration, volume estimation, and radiomic analysis. However, manual…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Pablo Rodriguez-Belenguer , Gloria Ribas , Javier Aquerreta Escribano , Rafael Moreno-Calatayud , Leonor Cerda-Alberich , Luis Marti-Bonmati

Magnetic Resonance Imaging (MRI) is widely used for screening and staging prostate cancer. However, many prostate cancers have subtle features which are not easily identifiable on MRI, resulting in missed diagnoses and alarming variability…

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

Background: Transrectal ultrasound guided systematic biopsies of the prostate is a routine procedure to establish a prostate cancer diagnosis. However, the 10-12 prostate core biopsies only sample a relatively small volume of the prostate,…

Image and Video Processing · Electrical Eng. & Systems 2022-04-20 Bojing Liu , Yinxi Wang , Philippe Weitz , Johan Lindberg , Johan Hartman , Lars Egevad , Henrik Grönberg , Martin Eklund , Mattias Rantalainen

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 being one of the frequently diagnosed malignancy in men, the rising demand for biopsies places a severe workload on pathologists. The grading procedure is tedious and subjective, motivating the development of automated…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Riddhasree Bhattacharyya , Pallabi Dutta , Sushmita Mitra

Radiologists often mix medical image reading strategies, including inspection of individual modalities and local image regions, using information at different locations from different images independently as well as concurrently. In this…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Xiangcen Wu , Shaheer U. Saeed , Yipei Wang , Ester Bonmati Coll , Yipeng Hu

With the wealth of medical image data, efficient curation is essential. Assigning the sequence type to magnetic resonance images is necessary for scientific studies and artificial intelligence-based analysis. However, incomplete or missing…

Image and Video Processing · Electrical Eng. & Systems 2024-08-01 Deepa Krishnaswamy , Bálint Kovács , Stefan Denner , Steve Pieper , David Clunie , Christopher P. Bridge , Tina Kapur , Klaus H. Maier-Hein , Andrey Fedorov

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

Detecting and segmenting brain metastases is a tedious and time-consuming task for many radiologists, particularly with the growing use of multi-sequence 3D imaging. This study demonstrates automated detection and segmentation of brain…

Image and Video Processing · Electrical Eng. & Systems 2019-12-30 Endre Grøvik , Darvin Yi , Michael Iv , Elisabeth Tong , Daniel L. Rubin , Greg Zaharchuk

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 one of the common diseases in men, and it is the most common malignant tumor in developed countries. Studies have shown that the male prostate incidence rate is as high as 2.5% to 16%, Currently, the inci-dence of…

Image and Video Processing · Electrical Eng. & Systems 2019-12-23 Xiangxiang Qin

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

Semantic segmentation constitutes an integral part of medical image analyses for which breakthroughs in the field of deep learning were of high relevance. The large number of trainable parameters of deep neural networks however renders them…

Computer Vision and Pattern Recognition · Computer Science 2017-02-28 Simon Kohl , David Bonekamp , Heinz-Peter Schlemmer , Kaneschka Yaqubi , Markus Hohenfellner , Boris Hadaschik , Jan-Philipp Radtke , Klaus Maier-Hein

The large number of trainable parameters of deep neural networks renders them inherently data hungry. This characteristic heavily challenges the medical imaging community and to make things even worse, many imaging modalities are ambiguous…

Neural and Evolutionary Computing · Computer Science 2017-11-29 Simon Kohl , David Bonekamp , Heinz-Peter Schlemmer , Kaneschka Yaqubi , Markus Hohenfellner , Boris Hadaschik , Jan-Philipp Radtke , Klaus Maier-Hein

We propose a novel automatic method for accurate segmentation of the prostate in T2-weighted magnetic resonance imaging (MRI). Our method is based on convolutional neural networks (CNNs). Because of the large variability in the shape, size,…

Image and Video Processing · Electrical Eng. & Systems 2020-01-01 Davood Karimi , Golnoosh Samei , Yanan Shao , Septimiu Salcudean

Prostate segmentation from magnetic resonance imaging (MRI) is a challenging task. In recent years, several network architectures have been proposed to automate this process and alleviate the burden of manual annotation. Although the…

Image and Video Processing · Electrical Eng. & Systems 2021-07-08 Dimitrios G. Zaridis , Eugenia Mylona , Nikolaos S. Tachos , Kostas Marias , Nikolaos Papanikolaou , Manolis Tsiknakis , Dimitrios I. Fotiadis

Prostate cancer represents a major threat to health. Early detection is vital in reducing the mortality rate among prostate cancer patients. One approach involves using multi-modality (CT, MRI, US, etc.) computer-aided diagnosis (CAD)…

Image and Video Processing · Electrical Eng. & Systems 2024-07-10 Rui Jin , Derun Li , Dehui Xiang , Lei Zhang , Hailing Zhou , Fei Shi , Weifang Zhu , Jing Cai , Tao Peng , Xinjian Chen

Prostate cancer is one of the most common forms of cancer and the third leading cause of cancer death in North America. As an integrated part of computer-aided detection (CAD) tools, diffusion-weighted magnetic resonance imaging (DWI) has…

Computer Vision and Pattern Recognition · Computer Science 2020-06-11 Sunghwan Yoo , Isha Gujrathi , Masoom A. Haider , Farzad Khalvati

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…