AIMC Topic: Image Processing, Computer-Assisted

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Improved food image recognition by leveraging deep learning and data-driven methods with an application to Central Asian Food Scene.

Scientific reports
The burden of diet-related diseases is high in Central Asia. In recent years, the field of food computing has gained prominence due to advancements in computer vision (CV) and the increasing use of smartphones and social media. These technologies pro...

SegMatch: semi-supervised surgical instrument segmentation.

Scientific reports
Surgical instrument segmentation is recognised as a key enabler in providing advanced surgical assistance and improving computer-assisted interventions. In this work, we propose SegMatch, a semi-supervised learning method to reduce the need for expen...

Single Molecule Localization Super-resolution Dataset for Deep Learning with Paired Low-resolution Images.

Scientific data
Deep learning super-resolution microscopy has advanced rapidly in recent years. Super-resolution images acquired by single molecule localization microscopy (SMLM) are ideal sources for high-quality datasets. However, the scarcity of public datasets l...

HindwingLib: A library of leaf beetle hindwings generated by Stable Diffusion and ControlNet.

Scientific data
The utilization of datasets from beetle hindwings is prevalent in research of morphology and evolution of beetles, serving as a valuable tool for comprehending the evolutionary processes and functional adaptations under specific environmental conditi...

Intelligent identification method of origin for Alismatis Rhizoma based on image and machine learning.

Scientific reports
Alismatis Rhizoma (AR) is widely utilized as a natural medicine across many Asian countries. However, in China, due to its complex origins, AR quality varies, which can affect clinical efficacy. Therefore, there is a need for a method that is both fa...

Bald eagle-optimized transformer networks with temporal-spatial mid-level features for pancreatic tumor classification.

Biomedical physics & engineering express
The classification and diagnosis of pancreatic tumors present significant challenges due to their inherent complexity and variability. Traditional methods often struggle to capture the dynamic nature of these tumors, highlighting the need for advance...

Meta-Analysis Informed Functional Connectomes Representations for Depression Identification.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Meta-analyses in neuroimaging have gained popularity. However, their clinical utility remains uncertain. Convergent masks, containing repeated clusters from publications, are often focal and small, and voxel-wise features can lead to the ...

Digital image processing combined with machine learning: A novel approach for bee pollen classification.

Food research international (Ottawa, Ont.)
The classification of bee pollen is crucial for ensuring product authenticity, quality control, and fraud prevention, particularly given the high commercial value of stingless bee pot-pollen. Although traditional pollen analysis methods are available...

SynMSE: A multimodal similarity evaluator for complex distribution discrepancy in unsupervised deformable multimodal medical image registration.

Medical image analysis
Unsupervised deformable multimodal medical image registration often confronts complex scenarios, which include intermodality domain gaps, multi-organ anatomical heterogeneity, and physiological motion variability. These factors introduce substantial ...

EfficientNet-Based Attention Residual U-Net With Guided Loss for Breast Tumor Segmentation in Ultrasound Images.

Ultrasound in medicine & biology
OBJECTIVE: Breast cancer poses a major health concern for women globally. Effective segmentation of breast tumors for ultrasound images is crucial for early diagnosis and treatment. Conventional convolutional neural networks have shown promising resu...