中文
相关论文

相关论文: Computerized Multiparametric MR image Analysis for…

200 篇论文

The diagnosis of prostate cancer faces a problem with overdiagnosis that leads to damaging side effects due to unnecessary treatment. Research has shown that the use of multi-parametric magnetic resonance images to conduct biopsies can…

图像与视频处理 · 电气工程与系统科学 2021-06-04 Pedro C. Neto

Prostate cancer (PCa) is the second most common cancer in men worldwide and the most frequently diagnosed cancer among men in more developed countries. The prognosis of PCa is excellent if detected at an early stage, making early screening…

医学物理 · 物理学 2021-09-14 Alexander Wong , Hayden Gunraj , Vignesh Sivan , Masoom A. Haider

Continuous biomarkers are common for disease screening and diagnosis. To reach a dichotomous clinical decision, a threshold would be imposed to distinguish subjects with disease from non-diseased individuals. Among various performance…

统计方法学 · 统计学 2021-04-21 Ziyi Li , Yijuan Huang , Dattatraya Patil , Martin G. Sanda

One of the distinct characteristics in radiologists' reading of multiparametric prostate MR scans, using reporting systems such as PI-RADS v2.1, is to score individual types of MR modalities, T2-weighted, diffusion-weighted, and dynamic…

图像与视频处理 · 电气工程与系统科学 2024-01-23 Wen Yan , Bernard Chiu , Ziyi Shen , Qianye Yang , Tom Syer , Zhe Min , Shonit Punwani , Mark Emberton , David Atkinson , Dean C. Barratt , Yipeng Hu

Prostate specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) imaging provides a tremendously exciting frontier in visualization of prostate cancer (PCa) metastatic lesions. However, accurate…

医学物理 · 物理学 2024-12-05 Amirhosein Toosi , Sara Harsini , François Bénard , Carlos Uribe , Arman Rahmim

The PI-CAI (Prostate Imaging: Cancer AI) challenge led to expert-level diagnostic algorithms for clinically significant prostate cancer detection. The algorithms receive biparametric MRI scans as input, which consist of T2-weighted and…

图像与视频处理 · 电气工程与系统科学 2024-07-01 Alessa Hering , Sarah de Boer , Anindo Saha , Jasper J. Twilt , Mattias P. Heinrich , Derya Yakar , Maarten de Rooij , Henkjan Huisman , Joeran S. Bosma

Effective surgical planning for breast cancer hinges on accurately predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). Diffusion-weighted MRI (DWI) and machine learning offer a non-invasive approach for early…

计算机视觉与模式识别 · 计算机科学 2024-04-09 Shir Nitzan , Maya Gilad , Moti Freiman

Prostate cancer is the second most common form of cancer, though most patients have a positive prognosis with many experiencing long-term survival with current treatment options. Yet, each treatment carries varying levels of intensity and…

定量方法 · 定量生物学 2024-10-31 Jefferson Zhou , Kahn Rhrissorrakrai

Diagnostic imaging has gained prominence as potential biomarkers for early detection and diagnosis in a diverse array of disorders including cancer. However, existing methods routinely face challenges arising from various factors such as…

Breast cancer is the most common malignant tumor among women and the second cause of cancer-related death. Early diagnosis in clinical practice is crucial for timely treatment and prognosis. Dynamic contrast-enhanced magnetic resonance…

图像与视频处理 · 电气工程与系统科学 2024-05-13 Zixian Li , Yuming Zhong , Yi Wang

Prostate cancer is the most common cancer in men worldwide and the second leading cause of cancer death in the United States. One of the prognostic features in prostate cancer is the Gleason grading of histopathology images. The Gleason…

图像与视频处理 · 电气工程与系统科学 2022-12-27 Mohammad Mahdi Behzadi , Mohammad Madani , Hanzhang Wang , Jun Bai , Ankit Bhardwaj , Anna Tarakanova , Harold Yamase , Ga Hie Nam , Sheida Nabavi

Active learning is considered a viable solution to alleviate the contradiction between the high dependency of deep learning-based segmentation methods on annotated data and the expensive pixel-level annotation cost of medical images.…

计算机视觉与模式识别 · 计算机科学 2024-10-23 Jun Shi , Shulan Ruan , Ziqi Zhu , Minfan Zhao , Hong An , Xudong Xue , Bing Yan

Magnetic Resonance Imaging (MRI) plays an important role in identifying clinically significant prostate cancer (csPCa), yet automated methods face challenges such as data imbalance, variable tumor sizes, and a lack of annotated data. This…

计算机视觉与模式识别 · 计算机科学 2025-05-01 Alessia Hu , Regina Beets-Tan , Lishan Cai , Eduardo Pooch

Automated grading of prostate cancer histopathology images is a challenging task, with one key challenge being the scarcity of annotations down to the level of regions of interest (strong labels), as typically the prostate cancer Gleason…

计算机视觉与模式识别 · 计算机科学 2018-11-20 Eirini Arvaniti , Manfred Claassen

Histopathological images (HIs) are the gold standard for evaluating some types of tumors for cancer diagnosis. The analysis of such images is not only time and resource consuming, but also very challenging even for experienced pathologists,…

To understand the biology of cancer, joint analysis of multiple data modalities, including imaging and genomics, is crucial. The involved nature of gene-microenvironment interactions necessitates the use of algorithms which treat both data…

信号处理 · 电气工程与系统科学 2018-02-27 Vaishnavi Subramanian , Benjamin Chidester , Jian Ma , Minh N. Do

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…

Prostate Cancer is one of the most frequently occurring cancers in men, with a low survival rate if not early diagnosed. PI-RADS reading has a high false positive rate, thus increasing the diagnostic incurred costs and patient discomfort.…

Early diagnosis of prostate cancer is crucial for efficient treatment. Multi-parametric Magnetic Resonance Images (mp-MRI) are widely used for lesion detection. The Prostate Imaging Reporting and Data System (PI-RADS) has standardized…

计算机视觉与模式识别 · 计算机科学 2023-08-21 Camille Ruppli , Pietro Gori , Roberto Ardon , Isabelle Bloch

A novel deep learning architecture (XmasNet) based on convolutional neural networks was developed for the classification of prostate cancer lesions, using the 3D multiparametric MRI data provided by the PROSTATEx challenge. End-to-end…

计算机视觉与模式识别 · 计算机科学 2017-03-14 Saifeng Liu , Huaixiu Zheng , Yesu Feng , Wei Li