[HTML][HTML] AI-driven 3D bioprinting for regenerative medicine: from bench to bedside
In recent decades, 3D bioprinting has garnered significant research attention due to its
ability to manipulate biomaterials and cells to create complex structures precisely. However …
ability to manipulate biomaterials and cells to create complex structures precisely. However …
A review: artificial intelligence in image-guided spinal surgery
J Zeng, Q Fu - Expert Review of Medical Devices, 2024 - Taylor & Francis
Introduction Due to the complex anatomy of the spine and the intricate surgical procedures
involved, spinal surgery demands a high level of technical expertise from surgeons. The …
involved, spinal surgery demands a high level of technical expertise from surgeons. The …
Understanding the Tricks of Deep Learning in Medical Image Segmentation: Challenges and Future Directions
Over the past few years, the rapid development of deep learning technologies for computer
vision has significantly improved the performance of medical image segmentation …
vision has significantly improved the performance of medical image segmentation …
DiffuX2CT: Diffusion Learning to Reconstruct CT Images from Biplanar X-Rays
Computed tomography (CT) is widely utilized in clinical settings because it delivers detailed
3D images of the human body. However, performing CT scans is not always feasible due to …
3D images of the human body. However, performing CT scans is not always feasible due to …
HDL: Hybrid deep learning for the synthesis of myocardial velocity maps in digital twins for cardiac analysis
Synthetic digital twins based on medical data accelerate the acquisition, labelling and
decision making procedure in digital healthcare. A core part of digital healthcare twins is …
decision making procedure in digital healthcare. A core part of digital healthcare twins is …
PRSCS-Net: Progressive 3D/2D rigid Registration network with the guidance of Single-view Cycle Synthesis
W Zhang, L Zhao, H Gou, Y Gong, Y Zhou… - Medical Image Analysis, 2024 - Elsevier
The 3D/2D registration for 3D pre-operative images (computed tomography, CT) and 2D
intra-operative images (X-ray) plays an important role in image-guided spine surgeries …
intra-operative images (X-ray) plays an important role in image-guided spine surgeries …
3DSRNet: 3D Spine Reconstruction Network Using 2D Orthogonal X-ray Images Based on Deep Learning
Orthopedic spine disease is one of the most common diseases in the clinic. The diagnosis of
spinal orthopedic injury is an important basis for the treatment of spinal orthopedic diseases …
spinal orthopedic injury is an important basis for the treatment of spinal orthopedic diseases …
MedM2G: Unifying Medical Multi-Modal Generation via Cross-Guided Diffusion with Visual Invariant
Medical generative models acknowledged for their high-quality sample generation ability
have accelerated the fast growth of medical applications. However recent works concentrate …
have accelerated the fast growth of medical applications. However recent works concentrate …
TRCT-GAN: CT reconstruction from biplane X-rays using transformer and generative adversarial networks
Computed tomography (CT) provides a three-dimensional view of a patient's internal
organs. Compared to CT volumes, X-ray imaging can significantly reduce the patient's …
organs. Compared to CT volumes, X-ray imaging can significantly reduce the patient's …
Perspective projection-based 3d CT reconstruction from biplanar X-rays
X-ray computed tomography (CT) is one of the most common imaging techniques used to
diagnose various diseases in the medical field. Its high contrast sensitivity and spatial …
diagnose various diseases in the medical field. Its high contrast sensitivity and spatial …