AIMC Topic: Deep Learning

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Enhancing HF-DL Model Validation for Liver Fibrosis Staging Through Sample Optimisation and Technical Integration.

Liver international : official journal of the International Association for the Study of the Liver
We read with great interest the article by Zhang et al. The study demonstrates that the deep learning model based on high-frequency ultrasound images significantly outperforms the low-frequency ultrasound model, FIB-4, APRI, and shear wave elastograp...

[AI-based applications in medical image computing].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
The processing of medical images plays a central role in modern diagnostics and therapy. Automated processing and analysis of medical images can efficiently accelerate clinical workflows and open new opportunities for improved patient care. However, ...

Bedside Ultrasound Vector Doppler Imaging System With GPU Processing and Deep Learning.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Recent innovations in vector flow imaging promise to bring the modality closer to clinical application and allow for more comprehensive, high frame-rate vascular assessments. One such innovation is plane-wave multi-angle vector Doppler, where pulsed ...

Development and validation of a SOTA-based system for biliopancreatic segmentation and station recognition system in EUS.

Surgical endoscopy
BACKGROUND: Endoscopic ultrasound (EUS) is a vital tool for diagnosing biliopancreatic disease, offering detailed imaging to identify key abnormalities. Its interpretation demands expertise, which limits its accessibility for less trained practitione...

Insights on Scan-Specific Deep-Learning Strategies for Brain MRI Parallel Imaging Reconstruction.

NMR in biomedicine
Scan-specific deep learning strategies have been proposed for parallel imaging reconstruction in which auto-calibrated signals (ACS) are used for training. Here, we introduce methods to objectively optimize architecture and training details. In addit...

Digitizing audiograms with deep learning: structured data extraction and pseudonymization for hearing big data.

Hearing research
PURPOSE: hearing loss relies on pure-tone audiometry (PTA); however, audiograms are often stored as unstructured images, limiting their integration into electronic medical records (EMRs) and common data models (CDMs). This study developed a deep lear...

Impact of Deep Learning-Based Image Conversion on Fully Automated Coronary Artery Calcium Scoring Using Thin-Slice, Sharp-Kernel, Non-Gated, Low-Dose Chest CT Scans: A Multi-Center Study.

Korean journal of radiology
OBJECTIVE: To evaluate the impact of deep learning-based image conversion on the accuracy of automated coronary artery calcium quantification using thin-slice, sharp-kernel, non-gated, low-dose chest computed tomography (LDCT) images collected from m...

Stabilization of the human heartbeat using adaptive controller-based optimized deep policy gradient.

Computers in biology and medicine
Stabilizing the cardiac rhythm is imperative for preserving cardiovascular health and preventing life-threatening arrhythmias. The stabilization of the heartbeat through traditional control methods presents significant challenges due to the intricate...

A review: Lightweight architecture model in deep learning approach for lung disease identification.

Computers in biology and medicine
As one of the leading causes of death worldwide, early detection of lung disease is a very important step to improve the effectiveness of treatment. By using medical image data, such as X-ray or CT-scan, classification of lung disease can be done. De...

An Artificial Intelligence Solution for Automated Dental Inspection and Charting.

International dental journal
BACKGROUND: Visual inspection and documentation (charting) of findings are critical components in dental practice. However, manual charting is tedious, time consuming, and prone to errors. Attempts to automate charting using AI have focused on comput...