A Performance Comparison of Different YOLOv7 Networks for High-Accuracy Cell Classification in Bronchoalveolar Lavage Fluid Utilising the Adam Optimiser and Label Smoothing [0.03%]
基于Adam优化器和标签平滑的支气管肺泡灌洗液高精度细胞分类的Different YOLOv7网络性能比较
Sebastian Rumpf,Nicola Zufall,Florian Rumpf et al.
Sebastian Rumpf et al.
Accurate classification of cells in bronchoalveolar lavage (BAL) fluid is essential for the assessment of lung disease in pneumology and critical care medicine. However, the effectiveness of BAL fluid analysis is highly dependent on individ...
Deep Learning-Based DCE-MRI Automatic Segmentation in Predicting Lesion Nature in BI-RADS Category 4 [0.03%]
基于深度学习的DCE-MRI自动分割在BI-RADS 4类病变性质预测中的价值研究
Tianyu Liu,Yurui Hu,Zehua Liu et al.
Tianyu Liu et al.
To investigate whether automatic segmentation based on DCE-MRI with a deep learning (DL) algorithm enabled advantages over manual segmentation in differentiating BI-RADS 4 breast lesions. A total of 197 patients with suspicious breast lesio...
A Systematic Review on the Use of Registration-Based Change Tracking Methods in Longitudinal Radiological Images [0.03%]
基于注册的纵向放射学图像变化跟踪方法的系统评价
Jeeho E Im,Muhammed Khalifa,Adriana V Gregory et al.
Jeeho E Im et al.
Registration is the process of spatially and/or temporally aligning different images. It is a critical tool that can facilitate the automatic tracking of pathological changes detected in radiological images and align images captured by diff...
Active Learning with Particle Swarm Optimization for Enhanced Skin Cancer Classification Utilizing Deep CNN Models [0.03%]
基于深度卷积神经网络模型的粒子群优化主动学习增强皮肤癌分类方法
Sayantani Mandal,Subhayu Ghosh,Nanda Dulal Jana et al.
Sayantani Mandal et al.
Skin cancer is a critical global health issue, with millions of non-melanoma and melanoma cases diagnosed annually. Early detection is essential to improving patient outcomes, yet traditional deep learning models for skin cancer classificat...
Pneumonia Detection from Chest X-Ray Images Using Deep Learning and Transfer Learning for Imbalanced Datasets [0.03%]
基于深度学习和迁移学习的不平衡数据集胸部X光图像肺炎检测方法研究
Faisal Alshanketi,Abdulrahman Alharbi,Mathew Kuruvilla et al.
Faisal Alshanketi et al.
Pneumonia remains a significant global health challenge, necessitating timely and accurate diagnosis for effective treatment. In recent years, deep learning techniques have emerged as powerful tools for automating pneumonia detection from c...
RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models [0.03%]
医疗图像分割模型的再现性、完整性、可靠性、泛化性和效率评估（RIDGE）
Farhad Maleki,Linda Moy,Reza Forghani et al.
Farhad Maleki et al.
Deep learning techniques hold immense promise for advancing medical image analysis, particularly in tasks like image segmentation, where precise annotation of regions or volumes of interest within medical images is crucial but manually labo...
A Comparison of Deep Learning vs. Dental Implantologists in Cone-Beam Computed Tomography-Based Bone Quality Classification [0.03%]
基于锥束CT的骨质量分类的深度学习与牙科植入专家的比较研究
Thatphong Pornvoranant,Wannakamon Panyarak,Kittichai Wantanajittikul et al.
Thatphong Pornvoranant et al.
Bone quality assessment is crucial for pre-surgical implant planning, influencing both implant design and drilling protocol selection. The Lekholm and Zarb (L&Z) classification, which categorizes bone quality into four types based on cortic...
MRI Radiomics-Based Machine Learning to Predict Lymphovascular Invasion of HER2-Positive Breast Cancer [0.03%]
基于MRI的影像组学机器学习预测HER2阳性乳腺癌的淋巴管血管浸润
Fang Han,Wenfei Li,Yurui Hu et al.
Fang Han et al.
This study aims to develop and prospectively validate radiomic models based on MRI to predict lymphovascular invasion (LVI) status in patients with HER2-positive breast cancer. A total of 225 patients with HER2-positive breast cancer who pr...
Improved Diagnostic Performance Using Dual-Energy CT-Derived Slope Parameter Images in Crohn's Disease [0.03%]
基于双源CT斜率参数图像在克罗恩病诊断效能中的优势
Min Hong,Ziying Lin,Hua Zhong et al.
Min Hong et al.
The objective of the study is to explore the image quality and diagnosis performance of the dual-energy CT-derived slope parameter images (SPI) generated by the algorithm based on the slope function in the diagnosis of Crohn's disease (CD)....
Technical Note: Neural Network Architectures for Self-Supervised Body Part Regression Models with Automated Localized Segmentation Application [0.03%]
技术报告：自监督身体部位回归模型与自动定位分割应用的神经网络架构
Michael Fei,Alan B McMillan
Michael Fei
The advancement of medical image deep learning necessitates tools that can accurately identify body regions from whole-body scans to serve as an essential pre-processing step for downstream tasks. Typically, these deep learning models rely ...