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相关论文: Deep Learning based Prediction of MSI using MMR Ma…

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Microsatellite instability (MSI) is a tumor phenotype whose diagnosis largely impacts patient care in colorectal cancers (CRC), and is associated with response to immunotherapy in all solid tumors. Deep learning models detecting MSI tumors…

图像与视频处理 · 电气工程与系统科学 2022-03-23 Charlie Saillard , Olivier Dehaene , Tanguy Marchand , Olivier Moindrot , Aurélie Kamoun , Benoit Schmauch , Simon Jegou

Microsatellite instability-high (MSI-H) is a tumor agnostic biomarker for immune checkpoint inhibitor therapy. However, MSI status is not routinely tested in prostate cancer, in part due to low prevalence and assay cost. As such, prediction…

Motivation: Microsatellite instability (MSI) is a cancer biomarker associated with cancer prognosis and chemotherapy sensitivity. Since the discovery of MSI, polymerase chain reaction (PCR)-based testing has been considered the gold…

基因组学 · 定量生物学 2023-04-17 Ji Detao , Liu Weier

Treatment approaches for colorectal cancer (CRC) are highly dependent on the molecular subtype, as immunotherapy has shown efficacy in cases with microsatellite instability (MSI) but is ineffective for the microsatellite stable (MSS)…

计算机视觉与模式识别 · 计算机科学 2024-11-13 Hadar Hezi , Matan Gelber , Alexander Balabanov , Yosef E. Maruvka , Moti Freiman

Assessing microsatellite stability status of a patient's colorectal cancer is crucial in personalizing treatment regime. Recently, convolutional-neural-networks (CNN) combined with transfer-learning approaches were proposed to circumvent…

计算机视觉与模式识别 · 计算机科学 2022-08-23 Daniel Shats , Hadar Hezi , Guy Shani , Yosef E. Maruvka , Moti Freiman

The prediction of microsatellite instability (MSI) and microsatellite stability (MSS) is essential in predicting both the treatment response and prognosis of gastrointestinal cancer. In clinical practice, a universal MSI testing is…

图像与视频处理 · 电气工程与系统科学 2022-01-14 Kaifeng Pang , Zuhayr Asad , Shilin Zhao , Yuankai Huo

Colorectal cancer (CRC) micro-satellite instability (MSI) prediction on histopathology images is a challenging weakly supervised learning task that involves multi-instance learning on gigapixel images. To date, radiology images have proven…

计算机视觉与模式识别 · 计算机科学 2024-01-17 Quan Liu , Jiawen Yao , Lisha Yao , Xin Chen , Jingren Zhou , Le Lu , Ling Zhang , Zaiyi Liu , Yuankai Huo

Microsatellite instability (MSI) is associated with several tumor types and its status has become increasingly vital in guiding patient treatment decisions. However, in clinical practice, distinguishing MSI from its counterpart is…

机器学习 · 统计学 2020-10-08 Jin Zhu , Wangwei Wu , Yuting Zhang , Shiyun Lin , Yukang Jiang , Ruixian Liu , Xueqin Wang

We present a system for the prediction of microsatellite instability (MSI) from H&E images of colorectal cancer using deep learning (DL) techniques customized for tissue microarrays (TMAs). The system incorporates an end-to-end image…

计算机视觉与模式识别 · 计算机科学 2021-10-29 Aurelia Bustos , Artemio Payá , Andres Torrubia , Rodrigo Jover , Xavier Llor , Xavier Bessa , Antoni Castells , Cristina Alenda

Considering the profound transformation affecting pathology practice, we aimed to develop a scalable artificial intelligence (AI) system to diagnose colorectal cancer from whole-slide images (WSI). For this, we propose a deep learning (DL)…

Based on global genomic status, the cancer tumor is classified as Microsatellite Instable (MSI) and Microsatellite Stable (MSS). Immunotherapy is used to diagnose MSI, whereas radiation and chemotherapy are used for MSS. Therefore, it is…

计算机视觉与模式识别 · 计算机科学 2025-02-18 Sai Venkatesh Chilukoti , Imran Hossen Md , Liqun Shan , Vijay Srinivas Tida , Xiali Hei

Several deep learning algorithms have been developed to predict survival of cancer patients using whole slide images (WSIs).However, identification of image phenotypes within the WSIs that are relevant to patient survival and disease…

图像与视频处理 · 电气工程与系统科学 2022-11-30 Xingyu Li , Jitendra Jonnagaddala , Min Cen , Hong Zhang , Xu Steven Xu

Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor problems for people with a detrimental effect on the functioning of the nervous system. In order to diagnose MS, multiple screening methods have been…

Artificial intelligence (AI) models have been developed for predicting clinically relevant biomarkers, including microsatellite instability (MSI), for colorectal cancers (CRC). However, the current deep-learning networks are data-hungry and…

定量方法 · 定量生物学 2024-12-24 Bangwei Guo , Xingyu Li , Jitendra Jonnagaddala , Hong Zhang , Xu Steven Xu

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…

In this work, a modified ResNet model is proposed for the classification of Microsatellite instability(MSI) and Microsatellite stability(MSS) of gastrointestinal cancer. The performance of this model is analyzed and compared with existing…

图像与视频处理 · 电气工程与系统科学 2022-02-07 CH Sai Venkatesh , Caleb Meriga , M. G. V. L Geethika , T Lakshmi Gayatri , V. B. K. L Aruna

The diagnosis, prognosis, and treatment of patients with musculoskeletal (MSK) disorders require radiology imaging (using computed tomography, magnetic resonance imaging(MRI), and ultrasound) and their precise analysis by expert…

图像与视频处理 · 电气工程与系统科学 2020-03-03 Ismail Irmakci , Syed Muhammad Anwar , Drew A. Torigian , Ulas Bagci

Cortical lesions (CLs) have emerged as valuable biomarkers in multiple sclerosis (MS), offering high diagnostic specificity and prognostic relevance. However, their routine clinical integration remains limited due to subtle magnetic…

Colorectal cancer (CRC) is a leading worldwide cause of cancer-related mortality, and the role of prompt precise detection is of paramount interest in improving patient outcomes. Conventional diagnostic methods such as colonoscopy and…

图像与视频处理 · 电气工程与系统科学 2025-10-29 Ovi Sarkar , Md Shafiuzzaman , Md. Faysal Ahamed , Golam Mahmud , Muhammad E. H. Chowdhury
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