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相关论文: An Efficient 3D Latent Diffusion Model for T1-cont…

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Objective: Gadolinium-based contrast agents (GBCAs) are commonly used in MRI scans of patients with gliomas to enhance brain tumor characterization using T1-weighted (T1W) MRI. However, there is growing concern about GBCA toxicity. This…

图像与视频处理 · 电气工程与系统科学 2024-09-04 Zach Eidex , Mojtaba Safari , Richard L. J. Qiu , David S. Yu , Hui-Kuo Shu , Hui Mao , Xiaofeng Yang

Contrast enhancement by Gadolinium-based contrast agents (GBCAs) is a vital tool for tumor diagnosis in neuroradiology. Based on brain MRI scans of glioblastoma before and after Gadolinium administration, we address enhancement prediction…

图像与视频处理 · 电气工程与系统科学 2024-10-14 Moritz Piening , Fabian Altekrüger , Gabriele Steidl , Elke Hattingen , Eike Steidl

\textit{Objective:} Gadolinium-based contrast agents (GBCAs) have been widely used to better visualize disease in brain magnetic resonance imaging (MRI). However, gadolinium deposition within the brain and body has raised safety concerns…

图像与视频处理 · 电气工程与系统科学 2022-07-19 Chao Chen , Catalina Raymond , Bill Speier , Xinyu Jin , Timothy F. Cloughesy , Dieter Enzmann , Benjamin M. Ellingson , Corey W. Arnold

Contrast-enhanced (CE) T1-weighted MRI is central to neuro-oncologic diagnosis but requires gadolinium-based agents, which add cost and scan time, raise environmental concerns, and may pose risks to patients. In this work, we propose a…

计算机视觉与模式识别 · 计算机科学 2025-08-19 Bastian Brandstötter , Erich Kobler

Gadolinium-based contrast agents (GBCAs) are central to glioma imaging but raise safety, cost, and accessibility concerns. Predicting contrast enhancement from non-contrast MRI using machine learning (ML) offers a safer alternative, as…

MRI-linear accelerator (MRI-Linac) systems allow for daily tracking of MRI changes during radiotherapy (RT). Since one common MRI-Linac operates at 0.35T, there are efforts towards developing protocols at that field strength. In this study…

Magnetic Resonance Imaging (MRI) enables the acquisition of multiple image contrasts, such as T1-weighted (T1w) and T2-weighted (T2w) scans, each offering distinct diagnostic insights. However, acquiring all desired modalities increases…

计算机视觉与模式识别 · 计算机科学 2025-07-22 Andrea Moschetto , Lemuel Puglisi , Alec Sargood , Pierluigi Dell'Acqua , Francesco Guarnera , Sebastiano Battiato , Daniele Ravì

Purpose: Apparent diffusion coefficient (ADC) maps derived from diffusion weighted (DWI) MRI provides functional measurements about the water molecules in tissues. However, DWI is time consuming and very susceptible to image artifacts,…

图像与视频处理 · 电气工程与系统科学 2024-07-08 Zach Eidex , Mojtaba Safari , Jacob Wynne , Richard L. J. Qiu , Tonghe Wang , David Viar Hernandez , Hui-Kuo Shu , Hui Mao , Xiaofeng Yang

Magnetic Resonance Spectroscopic Imaging (MRSI) is a non-invasive imaging technique for studying metabolism and has become a crucial tool for understanding neurological diseases, cancers and diabetes. High spatial resolution MRSI is needed…

Every year thousands of patients are diagnosed with a glioma, a type of malignant brain tumor. Physicians use MR images as a key tool in the diagnosis and treatment of these patients. Neural networks show great potential to aid physicians…

图像与视频处理 · 电气工程与系统科学 2019-10-03 Eric Carver , Zhenzhen Dai , Evan Liang , James Snyder , Ning Wen

Purpose/Objective: Brain tumors result in 20 years of lost life on average. Standard therapies induce complex structural changes in the brain that are monitored through MRI. Recent developments in artificial intelligence (AI) enable…

图像与视频处理 · 电气工程与系统科学 2026-03-10 Selena Huisman , Nordin Belkacemi , Vera Keil , Joost Verhoeff , Szabolcs David

Magnetic Resonance Spectroscopic Imaging (MRSI) is an essential tool for quantifying metabolites in the body, but the low spatial resolution limits its clinical applications. Deep learning-based super-resolution methods provided promising…

图像与视频处理 · 电气工程与系统科学 2022-07-22 Siyuan Dong , Gilbert Hangel , Eric Z. Chen , Shanhui Sun , Wolfgang Bogner , Georg Widhalm , Chenyu You , John A. Onofrey , Robin de Graaf , James S. Duncan

7 Tesla (7T) apparent diffusion coefficient (ADC) maps derived from diffusion-weighted imaging (DWI) demonstrate improved image quality and spatial resolution over 3 Tesla (3T) ADC maps. However, 7T magnetic resonance imaging (MRI)…

Purpose: Magnetic resonance imaging (MRI) exams include multiple series with varying contrast and redundant information. For instance, T2-FLAIR contrast is based upon tissue T2 decay and the presence of water, also present in T2- and…

Complete and high-quality multi-modal Magnetic Resonance Imaging (MRI) is essential for accurate neuro-oncological assessment, as each contrast provides complementary anatomical and pathological information. However, acquiring all…

图像与视频处理 · 电气工程与系统科学 2026-05-04 Zaid A. Abod , Furqan Aziz

High-resolution (HR) MRI scans obtained from research-grade medical centers provide precise information about imaged tissues. However, routine clinical MRI scans are typically in low-resolution (LR) and vary greatly in contrast and spatial…

图像与视频处理 · 电气工程与系统科学 2023-08-25 Jueqi Wang , Jacob Levman , Walter Hugo Lopez Pinaya , Petru-Daniel Tudosiu , M. Jorge Cardoso , Razvan Marinescu

Diffusion models have achieved remarkable quality in multi-modal MRI synthesis, but their computational cost (hundreds of sampling steps and separate models per modality) limits clinical deployment. We observe that this inefficiency stems…

计算机视觉与模式识别 · 计算机科学 2026-04-24 Yalcin Tur , Mihajlo Stojkovic , Ulas Bagci

T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) scans are important for diagnosis, treatment planning and monitoring of brain tumors. Depending on the brain tumor type, the FLAIR hyperintensity…

Objectives: To externally validate targeted T2 fluid-attenuated inversion recovery (T2-FLAIR) dropout for robust automated glioblastoma segmentation and whole-tumor volumetry without T2-FLAIR, while preserving performance when the full MRI…

图像与视频处理 · 电气工程与系统科学 2026-04-17 Marco Öchsner , Lena Kaiser , Robert Stahl , Nathalie L. Albert , Thomas Liebig , Robert Forbrig , Jonas Reis

Generative modelling of entire CT volumes conditioned on clinical reports has the potential to accelerate research through data augmentation, privacy-preserving synthesis and reducing regulator-constraints on patient data while preserving…

计算机视觉与模式识别 · 计算机科学 2025-08-19 Jiayi Wang , Hadrien Reynaud , Franciskus Xaverius Erick , Bernhard Kainz
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