AIMC Topic: Image Processing, Computer-Assisted

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ChatIOS: Improving automatic 3-dimensional tooth segmentation via GPT-4V and multimodal pre-training.

Journal of dentistry
OBJECTIVES: This study aims to propose a framework that integrates GPT-4V, a recent advanced version of ChatGPT, and multimodal pre-training techniques to enhance deep learning algorithms for 3-dimensional (3D) tooth segmentation in scans produced by...

Global-Local Transformer Network for Automatic Retinal Pathological Fluid Segmentation in Optical Coherence Tomography Images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: As a pivotal biomarker, the accurate segmentation of retinal pathological fluid such as intraretinal fluid (IRF), subretinal fluid (SRF), and pigment epithelial detachment (PED), was a critical task for diagnosis and treatme...

Quantifying axonal features of human superficial white matter from three-dimensional multibeam serial electron microscopy data assisted by deep learning.

NeuroImage
Short-range association fibers located in the superficial white matter play an important role in mediating higher-order cognitive function in humans. Detailed morphological characterization of short-range association fibers at the microscopic level p...

Artificial intelligence medical image-aided diagnosis system for risk assessment of adjacent segment degeneration after lumbar fusion surgery.

SLAS technology
The existing assessment of adjacent segment degeneration (ASD) risk after lumbar fusion surgery focuses on a single type of clinical information or imaging manifestations. In the early stages, it is difficult to show obvious degeneration characterist...

multiPI-TransBTS: A multi-path learning framework for brain tumor image segmentation based on multi-physical information.

Computers in biology and medicine
Brain Tumor Segmentation (BraTS) plays a critical role in clinical diagnosis, treatment planning, and monitoring the progression of brain tumors. However, due to the variability in tumor appearance, size, and intensity across different MRI modalities...

Generative adversarial networks in medical image reconstruction: A systematic literature review.

Computers in biology and medicine
PURPOSE: Recent advancements in generative adversarial networks (GANs) have demonstrated substantial potential in medical image processing. Despite this progress, reconstructing images from incomplete data remains a challenge, impacting image quality...

Interpretable deep learning method to predict wound healing progress based on collagen fibers in wound tissue.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: The dynamic evolution of collagen fibers during wound healing is crucial for assessing repair progression, guiding clinical treatment, and drug screening. Current quantitative methods analyzing collagen spatial patterns (den...

Towards robust multimodal ultrasound classification for liver tumor diagnosis: A generative approach to modality missingness.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In medical image analysis, combining multiple imaging modalities enhances diagnostic accuracy by providing complementary information. However, missing modalities are common in clinical settings, limiting the effectiveness of...

Neurocounter - A deep learning framework for high-fidelity spatial localization of neurons.

Journal of neuroscience methods
BACKGROUND: Many neuroscientific applications require robust and accurate localization of neurons. It is still an unsolved problem because of the enormous variation in intensity, texture, spatial overlap, morphology, and background artifacts. In addi...

GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Research in the cross-modal medical image translation domain has been very productive over the past few years in tackling the scarce availability of large curated multi-modality datasets with the promising performance of GAN...