AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 1461 to 1470 of 10288 articles

Machine learning-assisted assessment of municipal solid waste thermal treatment efficacy via rapid image recognition and visual analysis.

Waste management (New York, N.Y.)
Decentralized thermal treatment is a common method for municipal solid waste (MSW) disposal in rural areas. However, evaluating the effect of incineration has always been challenging owing to the difficult and time-consuming measurements involved. He...

A Hybrid Approach for Sports Activity Recognition Using Key Body Descriptors and Hybrid Deep Learning Classifier.

Sensors (Basel, Switzerland)
This paper presents an approach for event recognition in sequential images using human body part features and their surrounding context. Key body points were approximated to track and monitor their presence in complex scenarios. Various feature descr...

Optimizing hip MRI: enhancing image quality and elevating inter-observer consistency using deep learning-powered reconstruction.

BMC medical imaging
BACKGROUND: Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. L...

Genome-wide association study on color-image-based convolutional neural networks.

PeerJ
BACKGROUND: Convolutional neural networks have excellent modeling abilities to complex large-scale datasets and have been applied to genomics. It requires converting genotype data to image format when employing convolutional neural networks to genome...

Clinical Application of Deep Learning-Assisted Needles Reconstruction in Prostate Ultrasound Brachytherapy.

International journal of radiation oncology, biology, physics
PURPOSE: High dose rate (HDR) prostate brachytherapy (BT) procedure requires image-guided needle insertion. Given that general anesthesia is often employed during the procedure, minimizing overall planning time is crucial. In this study, we explore t...

Glo-net: A dual task branch based neural network for multi-class glomeruli segmentation.

Computers in biology and medicine
Accurate segmentation and classification of glomeruli are fundamental to histopathology slide analysis in renal pathology, which helps to characterize individual kidney disease. Accurate segmentation of glomeruli of different types faces two main cha...

Improving spleen segmentation in ultrasound images using a hybrid deep learning framework.

Scientific reports
This paper introduces a novel method for spleen segmentation in ultrasound images, using a two-phase training approach. In the first phase, the SegFormerB0 network is trained to provide an initial segmentation. In the second phase, the network is fur...

Not seeing the trees for the forest. The impact of neighbours on graph-based configurations in histopathology.

BMC bioinformatics
BACKGROUND: Deep learning (DL) has set new standards in cancer diagnosis, significantly enhancing the accuracy of automated classification of whole slide images (WSIs) derived from biopsied tissue samples. To enable DL models to process these large i...

Visualizing Preosteoarthritis: Updates on UTE-Based Compositional MRI and Deep Learning Algorithms.

Journal of magnetic resonance imaging : JMRI
Osteoarthritis (OA) is heterogeneous and involves structural changes in the whole joint, such as cartilage, meniscus/labrum, ligaments, and tendons, mainly with short T2 relaxation times. Detecting OA before the onset of irreversible changes is cruci...