AIMC Topic: Algorithms

Clear Filters Showing 16141 to 16150 of 28713 articles

Small Network for Lightweight Task in Computer Vision: A Pruning Method Based on Feature Representation.

Computational intelligence and neuroscience
Many current convolutional neural networks are hard to meet the practical application requirement because of the enormous network parameters. For accelerating the inference speed of networks, more and more attention has been paid to network compressi...

Radiologists in the loop: the roles of radiologists in the development of AI applications.

European radiology
OBJECTIVES: To examine the various roles of radiologists in different steps of developing artificial intelligence (AI) applications.

Interventional Radiology ex-machina: impact of Artificial Intelligence on practice.

La Radiologia medica
Artificial intelligence (AI) is a branch of Informatics that uses algorithms to tirelessly process data, understand its meaning and provide the desired outcome, continuously redefining its logic. AI was mainly introduced via artificial neural network...

A hybrid deep learning approach for gland segmentation in prostate histopathological images.

Artificial intelligence in medicine
BACKGROUND: In digital pathology, the morphology and architecture of prostate glands have been routinely adopted by pathologists to evaluate the presence of cancer tissue. The manual annotations are operator-dependent, error-prone and time-consuming....

Deep learning to segment pelvic bones: large-scale CT datasets and baseline models.

International journal of computer assisted radiology and surgery
PURPOSE: Pelvic bone segmentation in CT has always been an essential step in clinical diagnosis and surgery planning of pelvic bone diseases. Existing methods for pelvic bone segmentation are either hand-crafted or semi-automatic and achieve limited ...

Development and placement accuracy evaluation of an MR conditional robot for prostate intervention.

Medical & biological engineering & computing
Robot-assisted prostate intervention under magnetic resonance imaging (MRI) guidance is a promising method to improve the clinical performance compared with the manual method. An MR conditional 6-DOF prostate intervention serial robot is developed an...

Drone vs. Bird Detection: Deep Learning Algorithms and Results from a Grand Challenge.

Sensors (Basel, Switzerland)
Adopting effective techniques to automatically detect and identify small drones is a very compelling need for a number of different stakeholders in both the public and private sectors. This work presents three different original approaches that compe...

Data valuation for medical imaging using Shapley value and application to a large-scale chest X-ray dataset.

Scientific reports
The reliability of machine learning models can be compromised when trained on low quality data. Many large-scale medical imaging datasets contain low quality labels extracted from sources such as medical reports. Moreover, images within a dataset may...

A deep learning based multiscale approach to segment the areas of interest in whole slide images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This paper addresses the problem of liver cancer segmentation in Whole Slide Images (WSIs). We propose a multi-scale image processing method based on an automatic end-to-end deep neural network algorithm for the segmentation of cancerous areas. A sev...

DenseCapsNet: Detection of COVID-19 from X-ray images using a capsule neural network.

Computers in biology and medicine
At present, the global pandemic as it relates to novel coronavirus pneumonia is still a very difficult situation. Due to the recent outbreak of novel coronavirus pneumonia, novel chest X-ray (CXR) images that can be used for deep learning analysis ar...