AIMC Topic: Image Processing, Computer-Assisted

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Multi-step framework for glaucoma diagnosis in retinal fundus images using deep learning.

Medical & biological engineering & computing
Glaucoma is one of the most common causes of blindness in the world. Screening glaucoma from retinal fundus images based on deep learning is a common method at present. In the diagnosis of glaucoma based on deep learning, the blood vessels within the...

An attribution graph-based interpretable method for CNNs.

Neural networks : the official journal of the International Neural Network Society
Convolutional Neural Networks (CNNs) have demonstrated outstanding performance in various domains, such as face recognition, object detection, and image segmentation. However, the lack of transparency and limited interpretability inherent in CNNs pos...

Nanoscale single-vesicle analysis: High-throughput approaches through AI-enhanced super-resolution image analysis.

Biosensors & bioelectronics
The analysis of membrane vesicles at the nanoscale level is crucial for advancing the understanding of intercellular communication and its implications for health and disease. Despite their significance, the nanoscale analysis of vesicles at the sing...

Single-detector multiplex imaging flow cytometry for cancer cell classification with deep learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Imaging flow cytometry, which combines the advantages of flow cytometry and microscopy, has emerged as a powerful tool for cell analysis in various biomedical fields such as cancer detection. In this study, we develop multiplex imaging flow cytometry...

Research into the Applications of a Multi-Scale Feature Fusion Model in the Recognition of Abnormal Human Behavior.

Sensors (Basel, Switzerland)
Due to the increasing severity of aging populations in modern society, the accurate and timely identification of, and responses to, sudden abnormal behaviors of the elderly have become an urgent and important issue. In the current research on compute...

Enhancing the reliability of deep learning-based head and neck tumour segmentation using uncertainty estimation with multi-modal images.

Physics in medicine and biology
Deep learning shows promise in autosegmentation of head and neck cancer (HNC) primary tumours (GTV-T) and nodal metastases (GTV-N). However, errors such as including non-tumour regions or missing nodal metastases still occur. Conventional methods oft...

Lesion-Decoupling-Based Segmentation With Large-Scale Colon and Esophageal Datasets for Early Cancer Diagnosis.

IEEE transactions on neural networks and learning systems
Lesions of early cancers often show flat, small, and isochromatic characteristics in medical endoscopy images, which are difficult to be captured. By analyzing the differences between the internal and external features of the lesion area, we propose ...

Dynamic Loss Weighting for Multiorgan Segmentation in Medical Images.

IEEE transactions on neural networks and learning systems
Deep neural networks often suffer from performance inconsistency for multiorgan segmentation in medical images; some organs are segmented far worse than others. The main reason might be organs with different levels of learning difficulty for segmenta...

Automatic pipeline for segmentation of LV myocardium on quantitative MR T1 maps using deep learning model and computation of radial T1 and ECV values.

NMR in biomedicine
Native T1 mapping is a non-invasive technique used for early detection of diffused myocardial abnormalities, and it provides baseline tissue characterization. Post-contrast T1 mapping enhances tissue differentiation, enables extracellular volume (ECV...

Fully Automated Hippocampus Segmentation using T2-informed Deep Convolutional Neural Networks.

NeuroImage
Hippocampal atrophy (tissue loss) has become a fundamental outcome parameter in clinical trials on Alzheimer's disease. To accurately estimate hippocampus volume and track its volume loss, a robust and reliable segmentation is essential. Manual hippo...