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PUBLICATION

At AIMed, we strive to publish top-tier content in clinical and engineering journals, along with leading conferences in medical vision and medical image analysis. Our goal is to advance technology and medicine by disseminating cutting-edge research and fostering robust discussions across dynamic fields. We aim to connect with a global community to drive innovation and improve healthcare and engineering outcomes.

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2021

MRI-SegFlow V2.0: a novel unsupervised deep learning pipeline enabling accurate semantic segmentation of lumbar MR images with preliminary validation

Clinical

Xihe Kuang, Jason Cheung, Honghan Wu, Courtney, Jack, Richard, David, Teng Zhang

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2021

Light Field View Synthesis via Aperture Disparity and Warping Confidence Map

BME

Meng, Nan, Kai Li, Jianzhuang Liu, and Edmund Y. Lam

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2021

A Prospective Study of Grip Strength Trajectories and Incident Cardiovascular Disease

BME

Weida Liu, Runzhen Chen, Chenxi Song, Chuangshi Wang, Ge Chen, Jun Hao, Yang Wang, Chenxi Yu*

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2021

Application of deep learning upon spinal radiographs to predict progression in adolescent idiopathic scoliosis at first clinic visit

BME

Hongfei Wang, Teng Zhang*, Kenneth Man-Chee Cheung, Graham Ka-Hon Shea

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2021

The REDD1/TXNIP Complex Accelerates Oxidative Stress-Induced Apoptosis of Nucleus Pulposus Cells through the Mitochondrial Pathway

BME

Huipeng Yin, Kun Wang, Abhirup Das, Gaocai Li, Yu Song, Rongjin Luo, Jason Pui Yin Cheung, Teng Zhang, Shuai Li*, and Cao Yang*

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AIMED

We dedicate ourselves to non-invasive and intelligent solutions for spine care with advanced equipment and deep learning techniques. We are open and welcoming partners, researchers, engineers, etc worldwide.

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Level 5, Professorial Block, Queen Mary Hospital, Pok Fu Lam, Hong Kong SAR, China

Call Number

+852 3917 6987
+852 6067 1846

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