AIMC Topic: Image Processing, Computer-Assisted

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Rethinking masked image modelling for medical image representation.

Medical image analysis
Masked Image Modelling (MIM), a form of self-supervised learning, has garnered significant success in computer vision by improving image representations using unannotated data. Traditional MIMs typically employ a strategy of random sampling across th...

Face Omron Ring: Proactive defense against face forgery with identity awareness.

Neural networks : the official journal of the International Neural Network Society
In the era of Artificial Intelligence Generated Content (AIGC), face forgery models pose significant security threats. These models have caused widespread negative impacts through the creation of forged products targeting public figures, national lea...

Semantic segmentation in skin surface microscopic images with artifacts removal.

Computers in biology and medicine
Skin surface imaging has been used to examine skin lesions with a microscope for over a century and is commonly known as epiluminescence microscopy, dermatoscopy, or dermoscopy. Skin surface microscopy has been recommended to reduce the necessity of ...

An efficient colorectal cancer detection network using atrous convolution with coordinate attention transformer and histopathological images.

Scientific reports
The second most common type of malignant tumor worldwide is colorectal cancer. Histopathology image analysis offers crucial data for the clinical diagnosis of colorectal cancer. Currently, deep learning techniques are applied to enhance cancer classi...

Artificial intelligence in microplastic detection and pollution control.

Environmental research
The rising prevalence of microplastics (MPs) in various ecosystems has increased the demand for advanced detection and mitigation strategies. This review examines the integration of artificial intelligence (AI) with environmental science to improve m...

An efficient dual-domain deep learning network for sparse-view CT reconstruction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: We develop an efficient deep-learning based dual-domain reconstruction method for sparse-view CT reconstruction with small training parameters and comparable running time. We aim to investigate the model's capability and its...

A systematic review of few-shot learning in medical imaging.

Artificial intelligence in medicine
The lack of annotated medical images limits the performance of deep learning models, which usually need large-scale labelled datasets. Few-shot learning techniques can reduce data scarcity issues and enhance medical image analysis speed and robustnes...

Multi-class segmentation of temporomandibular joint using ensemble deep learning.

Scientific reports
Temporomandibular joint disorders are prevalent causes of orofacial discomfort. Diagnosis predominantly relies on assessing the configuration and positions of temporomandibular joint components in magnetic resonance images. The complex anatomy of the...

Construction and Validation of a General Medical Image Dataset for Pretraining.

Journal of imaging informatics in medicine
In the field of deep learning for medical image analysis, training models from scratch are often used and sometimes, transfer learning from pretrained parameters on ImageNet models is also adopted. However, there is no universally accepted medical im...