TransDiffSeg: Transformer-Based Conditional Diffusion Segmentation Model for Abdominal Multi-Objective [0.03%]
基于变压器的腹部多目标条件扩散分割模型 TransDiffSeg
WenWen Gu,GuoDong Zhang,RongHui Ju et al.
WenWen Gu et al.
In the domain of medical image segmentation, traditional diffusion probabilistic models are hindered by local inductive biases stemming from convolutional operations, constraining their ability to model long-term dependencies and leading to...
3D Features Fusion for Automated Segmentation of Fluid Regions in CSCR Patients: An OCT-based Photodynamic Therapy Response Analysis [0.03%]
基于OCT的光动力疗法反应分析中的CSCR患者液体区域自动化分割的3D特征融合方法
Elena Goyanes,Joaquim de Moura,José I Fernández-Vigo et al.
Elena Goyanes et al.
Central Serous Chorioretinopathy (CSCR) is a significant cause of vision impairment worldwide, with Photodynamic Therapy (PDT) emerging as a promising treatment strategy. The capability to precisely segment fluid regions in Optical Coherenc...
AG-MSTLN-EL: A Multi-source Transfer Learning Approach to Brain Tumor Detection [0.03%]
一种基于多源迁移学习的脑肿瘤检测方法
Shivaprasad Biradar,Virupakshappa
Shivaprasad Biradar
The analysis of medical images (MI) is an important part of advanced medicine as it helps detect and diagnose various diseases early. Classifying brain tumors through magnetic resonance imaging (MRI) poses a challenge demanding accurate mod...
RadImageNet and ImageNet as Datasets for Transfer Learning in the Assessment of Dental Radiographs: A Comparative Study [0.03%]
基于迁移学习的牙科放射线图像评估中的 RadImageNet 和 ImageNet 数据集比较研究
Shota Okazaki,Yuichi Mine,Yuki Yoshimi et al.
Shota Okazaki et al.
Transfer learning (TL) is an alternative approach to the full training of deep learning (DL) models from scratch and can transfer knowledge gained from large-scale data to solve different problems. ImageNet, which is a publicly available la...
MGB-Unet: An Improved Multiscale Unet with Bottleneck Transformer for Myositis Segmentation from Ultrasound Images [0.03%]
改进的多尺度U-Net与瓶颈变换器融合方法在超声图像中用于肌炎分割的方法(MGB-Unet)
Allaa Hussein,Sherin Youssef,Magdy A Ahmed et al.
Allaa Hussein et al.
Myositis is the inflammation of the muscles that can arise from various sources with diverse symptoms and require different treatments. For treatment to achieve optimal results, it is essential to obtain an accurate diagnosis promptly. This...
A Boundary-Enhanced Decouple Fusion Segmentation Network for Diagnosis of Adenomatous Polyps [0.03%]
一种边界增强的解耦融合分割网络的腺瘤息肉诊断方法
Jiaoju Wang,Haoran Feng,Alphonse Houssou Hounye et al.
Jiaoju Wang et al.
Adenomatous polyps, a common premalignant lesion, are often classified into villous adenoma (VA) and tubular adenoma (TA). VA has a higher risk of malignancy, whereas TA typically grows slowly and has a lower likelihood of cancerous transfo...
The Use of fMRI Regional Analysis to Automatically Detect ADHD Through a 3D CNN-Based Approach [0.03%]
基于三维卷积神经网络的ADHD自动检测方法及区域扫描分析
Perihan Gülşah Gülhan,Güzin Özmen
Perihan Gülşah Gülhan
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by a reduced attention span, hyperactivity, and impulsive behaviors, which typically manifest during childhood. This study employs functional mag...
Evaluating the Accuracy and Impact of the ESR-iGuide Decision Support Tool in Optimizing CT Imaging Referral Appropriateness [0.03%]
评估ESR-iGuide决策支持工具在优化CT影像转诊适宜性方面的准确性和影响
Osnat Luxenburg,Sharona Vaknin,Rachel Wilf-Miron et al.
Osnat Luxenburg et al.
Radiology referral quality impacts patient care, yet factors influencing quality are poorly understood. This study assessed the quality of computed tomography (CT) referrals, identified associated characteristics, and evaluated the ESR-iGui...
Policy Learning for Actively Labeled Sample Selection on Lumbar Semi-supervised Classification [0.03%]
主动标记样本选择的政策学习在腰椎半监督分类中的应用
Jinjin Hai,Jian Chen,Kai Qiao et al.
Jinjin Hai et al.
Large labeled data bring significant performance improvement, but acquiring labeled medical data is particularly challenging due to the laborious, time-consuming, and medically qualified annotation. Semi-supervised learning has been employe...
Enhanced Domain Adaptation for Foot Ulcer Segmentation Through Mixing Self-Trained Weak Labels [0.03%]
通过混合自训练弱标签改进域适应以进行足溃疡分割
David Jozef Hresko,Peter Drotar,Quoc Cuong Ngo et al.
David Jozef Hresko et al.
Wound management requires the measurement of the wound parameters such as its shape and area. However, computerized analysis of the wound suffers the challenge of inexact segmentation of the wound images due to limited or inaccurate labels....