AIMC Topic: Image Processing, Computer-Assisted

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Cluster-CAM: Cluster-weighted visual interpretation of CNNs' decision in image classification.

Neural networks : the official journal of the International Neural Network Society
Despite the tremendous success of convolutional neural networks (CNNs) in computer vision, the mechanism of CNNs still lacks clear interpretation. Currently, class activation mapping (CAM), a famous visualization technique to interpret CNN's decision...

Clothing-invariant contrastive learning for unsupervised person re-identification.

Neural networks : the official journal of the International Neural Network Society
Clothing change person re-identification (CC-ReID) aims to match images of the same person wearing different clothes across diverse scenes. Leveraging biological features or clothing labels, existing CC-ReID methods have demonstrated promising perfor...

Using diffusion models to generate synthetic labeled data for medical image segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: Medical image analysis has become a prominent area where machine learning has been applied. However, high-quality, publicly available data are limited either due to patient privacy laws or the time and cost required for experts to annotate i...

A Microvascular Segmentation Network Based on Pyramidal Attention Mechanism.

Sensors (Basel, Switzerland)
The precise segmentation of retinal vasculature is crucial for the early screening of various eye diseases, such as diabetic retinopathy and hypertensive retinopathy. Given the complex and variable overall structure of retinal vessels and their delic...

Literature Review of Deep-Learning-Based Detection of Violence in Video.

Sensors (Basel, Switzerland)
Physical aggression is a serious and widespread problem in society, affecting people worldwide. It impacts nearly every aspect of life. While some studies explore the root causes of violent behavior, others focus on urban planning in high-crime areas...

Automatic classification of normal and abnormal cell division using deep learning.

Scientific reports
In recent years, there has been a surge in the development of methods for cell segmentation and tracking, with initiatives like the Cell Tracking Challenge driving progress in the field. Most studies focus on regular cell population videos in which c...

Improving difficult direct laryngoscopy prediction using deep learning and minimal image analysis: a single-center prospective study.

Scientific reports
Accurate prediction of difficult direct laryngoscopy (DDL) is essential to ensure optimal airway management and patient safety. The present study proposed an AI model that would accurately predict DDL using a small number of bedside pictures of the p...

An improved approach for automated cervical cell segmentation with PointRend.

Scientific reports
Regular screening for cervical cancer is one of the best tools to reduce cancer incidence. Automated cell segmentation in screening is an essential task because it can present better understanding of the characteristics of cervical cells. The main ch...

Multi-modal segmentation with missing image data for automatic delineation of gross tumor volumes in head and neck cancers.

Medical physics
BACKGROUND: Head and neck (HN) gross tumor volume (GTV) auto-segmentation is challenging due to the morphological complexity and low image contrast of targets. Multi-modality images, including computed tomography (CT) and positron emission tomography...