Retina Blood Vessels Segmentation and Classification with the Multi-featured Approach [0.03%]
基于多重特征的视网膜血管分割及分类方法
Usharani Bhimavarapu
Usharani Bhimavarapu
Segmenting retinal blood vessels poses a significant challenge due to the irregularities inherent in small vessels. The complexity arises from the intricate task of effectively merging features at multiple levels, coupled with potential spa...
Automated 3D Cobb Angle Measurement Using U-Net in CT Images of Preoperative Scoliosis Patients [0.03%]
基于U-Net的术前脊柱侧弯患者CT图像自动三维Cobb角测量方法研究
Lening Li,Teng Zhang,Fan Lin et al.
Lening Li et al.
To propose a deep learning framework "SpineCurve-net" for automated measuring the 3D Cobb angles from computed tomography (CT) images of presurgical scoliosis patients. A total of 116 scoliosis patients were analyzed, divided into a trainin...
IEA-Net: Internal and External Dual-Attention Medical Segmentation Network with High-Performance Convolutional Blocks [0.03%]
基于高性能卷积块的内部外部双重注意医学分割网络
Bincheng Peng,Chao Fan
Bincheng Peng
Currently, deep learning is developing rapidly in the field of image segmentation, and medical image segmentation is one of the key applications in this field. Conventional CNN has achieved great success in general medical image segmentatio...
Heatmap-Based Active Shape Model for Landmark Detection in Lumbar X-ray Images [0.03%]
基于热度图的主动形状模型在腰椎X射线图像中的定位问题研究
Minho Choi,Jun-Su Jang
Minho Choi
Medical staff inspect lumbar X-ray images to diagnose lumbar spine diseases, and the analysis process is currently automated using deep-learning techniques. The detection of landmarks is necessary in the automatic process of localizing the ...
Mana Moassefi
Mana Moassefi
DEAF-Net: Detail-Enhanced Attention Feature Fusion Network for Retinal Vessel Segmentation [0.03%]
用于视网膜血管分割的细节增强注意力特征融合网络(DEAF-Net)
Pengfei Cai,Biyuan Li,Gaowei Sun et al.
Pengfei Cai et al.
Retinal vessel segmentation is crucial for the diagnosis of ophthalmic and cardiovascular diseases. However, retinal vessels are densely and irregularly distributed, with many capillaries blending into the background, and exhibit low contra...
Airway and Airway Obstruction Site Segmentation Study Using U-Net with Drug-Induced Sleep Endoscopy Images [0.03%]
基于药物诱发睡眠内镜图像的U-Net气道及气道梗阻部位分割研究
Yeong Hun Kang,Jin Youp Kim,Young Jae Kim et al.
Yeong Hun Kang et al.
Obstructive sleep apnea is characterized by a decrease or cessation of breathing due to repetitive closure of the upper airway during sleep, leading to a decrease in blood oxygen saturation. In this study, employing a U-Net model, we utiliz...
Let UNet Play an Adversarial Game: Investigating the Effect of Adversarial Training in Enhancing Low-Resolution MRI [0.03%]
让UNet玩一场对抗游戏：通过对抗训练提高低分辨率MRI效果的研究
Mohammad Javadi,Rishabh Sharma,Panagiotis Tsiamyrtzis et al.
Mohammad Javadi et al.
Adversarial training has attracted much attention in enhancing the visual realism of images, but its efficacy in clinical imaging has not yet been explored. This work investigated adversarial training in a clinical context, by training 206 ...
Neil Chatterjee,Jeffrey Duda,James Gee et al.
Neil Chatterjee et al.
Although numerous AI algorithms have been published, the relatively small number of algorithms used clinically is partly due to the difficulty of implementing AI seamlessly into the clinical workflow for radiologists and for their healthcar...
AutoCorNN: An Unsupervised Physics-Aware Deep Learning Model for Geometric Distortion Correction of Brain MRI Images Towards MR-Only Stereotactic Radiosurgery [0.03%]
自监督物理感知深度学习模型AutoCorNN：用于脑部MRI图像几何失真校正的模型，面向单纯使用磁共振立体定向放射外科手术
Mahboube Sadat Hosseini,Seyed Mahmoud Reza Aghamiri,Ali Fatemi Ardekani et al.
Mahboube Sadat Hosseini et al.
Geometric distortions in brain MRI images arising from susceptibility artifacts at air-tissue interfaces pose a significant challenge for high-precision radiation therapy modalities like stereotactic radiosurgery, necessitating sub-millimet...