A Domain-Shift Invariant CNN Framework for Cardiac MRI Segmentation Across Unseen Domains [0.03%]
一种跨未知领域的 cardiac mri 分割的域迁移不变 cnn 框架
Sanjeet S Patil,Manojkumar Ramteke,Mansi Verma et al.
Sanjeet S Patil et al.
The emergence of various deep learning approaches in diagnostic medical image segmentation has made machines capable of accomplishing human-level accuracy. However, the generalizability of these architectures across patients from different ...
Virtual Three-Dimensional Model Analysis in the Assessment of the Maxillary and Mandibular Donor Sites on Cone-Beam Computed Tomography Images [0.03%]
基于锥形束CT图像的虚拟三维模型在上颌和下颌供区评估中的应用分析
Seyed Moein Diarjani,Safa Motevasseli,Zahra Dalili Kajan
Seyed Moein Diarjani
Using the Mimics software to assess the maxillary and mandibular donor sites on cone-beam computed tomography (CBCT) images. This cross-sectional study was conducted on 80 CBCT scans. Data in DICOM format were transferred to the Mimics soft...
Deep Learning-Based Skin Lesion Multi-class Classification with Global Average Pooling Improvement [0.03%]
基于全局平均池化改进的深度学习皮肤病变多分类技术
Paravatham V S P Raghavendra,C Charitha,K Ghousiya Begum et al.
Paravatham V S P Raghavendra et al.
Cancerous skin lesions are one of the deadliest diseases that have the ability in spreading across other body parts and organs. Conventionally, visual inspection and biopsy methods are widely used to detect skin cancers. However, these meth...
Efficient Collaboration Between Radiologists Using the PACS-Integrated Refer Function to Reduce Communication Times [0.03%]
利用PACS集成参考功能提高放射科医生协作效率 降低通信时间
Seungsoo Lee,Eun-Kyung Kim,Soo Yoon Chung et al.
Seungsoo Lee et al.
The purpose of this study was to assess the utility of a picture archiving and communication systems (PACS)-integrated refer function for improving collaboration between radiologists and radiographers during daily reading sessions. Retrospe...
Artificial Intelligence Application to Screen Abdominal Aortic Aneurysm Using Computed tomography Angiography [0.03%]
基于CTA的AI主动脉瘤筛查技术
Giovanni Spinella,Alice Fantazzini,Alice Finotello et al.
Giovanni Spinella et al.
The aim of our study is to validate a totally automated deep learning (DL)-based segmentation pipeline to screen abdominal aortic aneurysms (AAA) in computed tomography angiography (CTA) scans. We retrospectively evaluated 73 thoraco-abdomi...
Automated Rib Fracture Detection on Chest X-Ray Using Contrastive Learning [0.03%]
基于对比学习的胸部X光肋骨骨折自动化检测方法研究
Hongbiao Sun,Xiang Wang,Zheren Li et al.
Hongbiao Sun et al.
To develop a deep learning-based model for detecting rib fractures on chest X-Ray and to evaluate its performance based on a multicenter study. Chest digital radiography (DR) images from 18,631 subjects were used for the training, testing, ...
Multicenter Study
Journal of digital imaging. 2023 Oct;36(5):2138-2147. DOI:10.1007/s10278-023-00868-z 2023
Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review [0.03%]
深度学习算法在医学影像分析中的再现性系统综述
Mana Moassefi,Pouria Rouzrokh,Gian Marco Conte et al.
Mana Moassefi et al.
Since 2000, there have been more than 8000 publications on radiology artificial intelligence (AI). AI breakthroughs allow complex tasks to be automated and even performed beyond human capabilities. However, the lack of details on the method...
Jinli Yuan,Feng Zhou,Zhitao Guo et al.
Jinli Yuan et al.
Low-dose computed tomography (LDCT) is an effective way to reduce radiation exposure for patients. However, it will increase the noise of reconstructed CT images and affect the precision of clinical diagnosis. The majority of the current de...
Functional Connectivity Networks with Latent Distributions for Mild Cognitive Impairment Identification [0.03%]
基于潜在分布的轻度认知障碍功能连接网络识别方法
Qiling Tang,Yuhong Lu,Bilian Cai et al.
Qiling Tang et al.
This work presents a novel approach to estimate brain functional connectivity networks via generative learning. Due to the complexity and variability of rs-fMRI signal, we consider it as a random variable, and utilize variational autoencode...
COVID-19 Severity Prediction from Chest X-ray Images Using an Anatomy-Aware Deep Learning Model [0.03%]
基于解剖感知深度学习模型的胸部X光图像新冠肺炎病情预测
Nusrat Binta Nizam,Sadi Mohammad Siddiquee,Mahbuba Shirin et al.
Nusrat Binta Nizam et al.
The COVID-19 pandemic has been adversely affecting the patient management systems in hospitals around the world. Radiological imaging, especially chest x-ray and lung Computed Tomography (CT) scans, plays a vital role in the severity analys...