AIMC Topic: Image Processing, Computer-Assisted

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Co-Mask R-CNN: collaborative learning-based method for tooth instance segmentation.

The Journal of clinical pediatric dentistry
Traditional tooth image analysis methods primarily focus on feature extraction from individual images, often overlooking critical tooth shape and position information. This paper presents a novel computer-aided diagnosis method, Collaborative learnin...

Automated dentition segmentation: 3D UNet-based approach with MIScnn framework.

Journal of the World federation of orthodontists
INTRODUCTION: Advancements in technology have led to the adoption of digital workflows in dentistry, which require the segmentation of regions of interest from cone-beam computed tomography (CBCT) scans. These segmentations assist in diagnosis, treat...

Tensorial multiview low-rank high-order graph learning for context-enhanced domain adaptation.

Neural networks : the official journal of the International Neural Network Society
Unsupervised Domain Adaptation (UDA) is a machine learning technique that facilitates knowledge transfer from a labeled source domain to an unlabeled target domain, addressing distributional discrepancies between these domains. Existing UDA methods o...

Cardiac motion correction with a deep learning network for perfusion defect assessment in single-photon emission computed tomography myocardial perfusion imaging.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: In myocardial perfusion imaging (MPI) with single-photon emission computed tomography (SPECT), ungated studies are used for evaluation of perfusion defects despite motion blur. We investigate the potential benefit of motion correction usi...

A deep learning approach for ovarian cancer detection and classification based on fuzzy deep learning.

Scientific reports
Different oncologists make their own decisions about the detection and classification of the type of ovarian cancer from histopathological whole slide images. However, it is necessary to have an automated system that is more accurate and standardized...

Enhancing MRI brain tumor classification: A comprehensive approach integrating real-life scenario simulation and augmentation techniques.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Brain cancer poses a significant global health challenge, with mortality rates showing a concerning surge over recent decades. The incidence of brain cancer-related mortality has risen from 140,000 to 250,000, accompanied by a doubling in new diagnos...

Toward high-quality pseudo masks from noisy or weak annotations for robust medical image segmentation.

Neural networks : the official journal of the International Neural Network Society
Deep learning networks excel in image segmentation with abundant accurately annotated training samples. However, in medical applications, acquiring large quantities of high-quality labeled images is prohibitively expensive. Thus, learning from imperf...

Automated tablet defect detection and the prediction of disintegration time and crushing strength with deep learning based on tablet surface images.

International journal of pharmaceutics
This paper presents novel measurement methods, where deep learning was used to detect tableting defects and determine the crushing strength and disintegration time of tablets on images captured by machine vision. Five different classes of defects wer...

Editorial: Artificial Intelligence (AI), Digital Image Analysis, and the Future of Cancer Diagnosis and Prognosis.

Medical science monitor : international medical journal of experimental and clinical research
On October 8 2024, the Royal Swedish Academy of Sciences announced the 2024 Nobel Prize in Physics was awarded to Hopfield and Hinton for their foundation research on machine learning with artificial neural networks, which resulted in the current app...

ACL-DUNet: A tumor segmentation method based on multiple attention and densely connected breast ultrasound images.

PloS one
Breast cancer is the most common cancer in women. Breast masses are one of the distinctive signs for diagnosing breast cancer, and ultrasound is widely used for screening as a non-invasive and effective method for breast examination. In this study, w...