AIMC Topic: Deep Learning

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Automated classification of cells into multiple classes in epithelial tissue of oral squamous cell carcinoma using transfer learning and convolutional neural network.

Neural networks : the official journal of the International Neural Network Society
The analysis of tissue of a tumor in the oral cavity is essential for the pathologist to ascertain its grading. Recent studies using biopsy images reveal computer-aided diagnosis for oral sub-mucous fibrosis (OSF) carried out using machine learning a...

nucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer.

Cell systems
Single-cell segmentation is typically a crucial task of image-based cellular analysis. We present nucleAIzer, a deep-learning approach aiming toward a truly general method for localizing 2D cell nuclei across a diverse range of assays and light micro...

Web-based fully automated cephalometric analysis by deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: An accurate lateral cephalometric analysis is vital in orthodontic diagnosis. Identification of anatomic landmarks on lateral cephalograms is tedious, and errors may occur depending on the doctor's experience. Several attemp...

Deep learning-based pancreas segmentation and station recognition system in EUS: development and validation of a useful training tool (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: EUS is considered one of the most sensitive modalities for pancreatic cancer detection, but it is highly operator-dependent and the learning curve is steep. In this study, we constructed a system named BP MASTER (pancreaticobilia...

Semi-supervised labelling of the femur in a whole-body post-mortem CT database using deep learning.

Computers in biology and medicine
A deep learning pipeline was developed and used to localize and classify a variety of implants in the femur contained in whole-body post-mortem computed tomography (PMCT) scans. The results provide a proof-of-principle approach for labelling content ...

Deep learning-based anatomical site classification for upper gastrointestinal endoscopy.

International journal of computer assisted radiology and surgery
PURPOSE: Upper gastrointestinal (GI) endoscopic image documentation has provided an efficient, low-cost solution to address quality control for endoscopic reporting. The problem is, however, challenging for computer-assisted techniques, because diffe...

A review on segmentation of knee articular cartilage: from conventional methods towards deep learning.

Artificial intelligence in medicine
In this paper, we review the state-of-the-art approaches for knee articular cartilage segmentation from conventional techniques to deep learning (DL) based techniques. Knee articular cartilage segmentation on magnetic resonance (MR) images is of grea...

COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches.

Computers in biology and medicine
Coronavirus causes a wide variety of respiratory infections and it is an RNA-type virus that can infect both humans and animal species. It often causes pneumonia in humans. Artificial intelligence models have been helpful for successful analyses in t...