AIMC Topic: Deep Learning

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Multi-step depth enhancement refine network with multi-view stereo.

PloS one
This paper introduces an innovative multi-view stereo matching network-the Multi-Step Depth Enhancement Refine Network (MSDER-MVS), aimed at improving the accuracy and computational efficiency of high-resolution 3D reconstruction. The MSDER-MVS netwo...

Association of visceral fat obesity with structural change in abdominal organs: fully automated three-dimensional volumetric computed tomography measurement using deep learning.

Abdominal radiology (New York)
The purpose of this study was to explore the association between structural changes in abdominal organs and visceral fat obesity (VFO) using a fully automated three-dimensional (3D) volumetric computed tomography (CT) measurement method based on deep...

Visualizing what's missing: Using deep learning and Bow-Tie diagrams to identify and visualize missing leading indicators in industrial construction.

Journal of safety research
INTRODUCTION: In the construction industry, where safety is paramount, the frequency and severity of workplace incidents remain critical concerns. Therefore, site safety inspections have become essential for health and safety programs. While incident...

A novel method for online sex sorting of silkworm pupae (Bombyx mori) using computer vision combined with deep learning.

Journal of the science of food and agriculture
BACKGROUND: Silkworm pupae (SP), the pupal stage of an edible insect, have strong potential in the food, medicine, and cosmetic industries. Sex sorting is essential to enhance nutritional content and genetic traits in SP crossbreeding but it remains ...

A Review of ChatGPT as a Reliable Source of Scientific Information Regarding Endodontic Local Anesthesia.

Journal of endodontics
INTRODUCTION: ChatGPT is an artificial intelligence chatbot, developed by OpenAI, which uses Deep Learning technology for information processing. The chatbot uses natural language processing and machine learning algorithms to respond to users' questi...

Deep learning-based clustering for endotyping and post-arthroplasty response classification using knee osteoarthritis multiomic data.

Annals of the rheumatic diseases
OBJECTIVES: Primary knee osteoarthritis (KOA) is a heterogeneous disease with clinical and molecular contributors. Biofluids contain microRNAs and metabolites that can be measured by omic technologies. Multimodal deep learning is adept at uncovering ...

FakET: Simulating cryo-electron tomograms with neural style transfer.

Structure (London, England : 1993)
In cryo-electron microscopy, accurate particle localization and classification are imperative. Recent deep learning solutions, though successful, require extensive training datasets. The protracted generation time of physics-based models, often emplo...

Image quality and diagnostic performance of deep learning reconstruction for diffusion- weighted imaging in 3 T breast MRI.

European journal of radiology
PURPOSE: This study aimed to assess the image quality and the diagnostic value of deep learning reconstruction (DLR) for diffusion-weighted imaging (DWI) compared with conventional single-shot echo-planar imaging (ss-EPI) in 3 T breast MRI.

Artificial intelligence in gastrointestinal cancer research: Image learning advances and applications.

Cancer letters
With the rapid advancement of artificial intelligence (AI) technologies, including deep learning, large language models, and neural networks, these methodologies are increasingly being developed and integrated into cancer research. Gastrointestinal t...

EAMAPG: Explainable Adversarial Model Analysis via Projected Gradient Descent.

Computers in biology and medicine
Despite the outstanding performance of deep learning (DL) models, their interpretability remains a challenging topic. In this study, we address the transparency of DL models in medical image analysis by introducing a novel interpretability method usi...