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Imaging equipment

A convenient method for the accurate identification of Citri Reticulatae Pericarpium using image and multi-stream

Zhiyi Wu, Tianshu Wang, [ ... ], Xichen Yang

Pneumonia and pneumothorax detection: A multi-factor evaluation of chest X-rays

Yousef Saad Aldabayan

Assessing the clinical relevance of point-of-care ultrasound for hospitalists: Influence on clinical reasoning and decision-making

Maira Dias Souza, Hassan Rahhal, Iolanda F. L. C. Tibério

Optimizing autofocus under multispectral lighting via enhanced SIFT and Pearson correlation coefficient

Chao Ma, Mingkun Zhang, [ ... ], Yongyi Yan

Deep learning-based automated detection of supernumerary teeth in pediatric panoramic radiographs

İlhan Uzel, Behrang Ghabchi, Dilşah Çoğulu

Multi-scale error-driven dense residual network for image super-resolution reconstruction

Xueri Li, Lei Yang, Shimin Liang, Jianfang Wu

Comparison of angle-closure detection between automated gonioscopy and anterior-segment optical coherence tomography

Yuki Takagi, Ryo Asano, [ ... ], Kazuo Ichikawa

Novel imaging diagnosis of neuropsychiatric systemic lupus erythematosus using topological data analysis: A retrospective study

Kayoko Urashima, Kunihiro Ichinose, [ ... ], Masao Ueki

Effects of Er: YAG laser and acid etching on bond strength of clear aligner attachments to fluorotic enamel

Rui Xia, Jie Lei, Maoxuan Luo, Yao Xiao

Widespread misidentification of scanning electron microscope instruments in the peer-reviewed materials science and engineering literature

Reese A. K. Richardson, Jeonghyun Moon, Spencer S. Hong, Luís A. Nunes Amaral

Research on equipment fault diagnosis model based on gan and inverse PINN: Solutions for data imbalance and rare faults

Jian Deng, Zheng Cheng, Aiming Gu, Shibohua Zhang

Proof of concept pilot study to assess the utility of magnetic resonance extra-cellular volume quantification to diagnose advanced liver disease in people with Cystic Fibrosis

Daniel H. Tewkesbury, Jennifer A. Scott, [ ... ], Varinder S. Athwal

Fast fault diagnosis of smart grid equipment based on deep neural network model based on knowledge graph

Lin Jun, Zhou Chenliang

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