AIMC Topic: Deep Learning
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Self-supervised learning for label-free segmentation in cardiac ultrasound.
Nature communications
Apr 30, 2025
Segmentation and measurement of cardiac chambers from ultrasound is critical, but laborious and poorly reproducible. Neural networks can assist, but supervised approaches require the same problematic manual annotations. We build a pipeline for self-s...
3D tooth identification for forensic dentistry using deep learning.
BMC oral health
Apr 30, 2025
The classification of intraoral teeth structures is a critical component in modern dental analysis and forensic dentistry. Traditional methods, relying on 2D imaging, often suffer from limitations in accuracy and comprehensiveness due to the complex ...
High-Precision Intelligent Diagnosis of Pancreatic Cancer: Flowing Diffuseness from Single to Whole.
Analytical chemistry
Apr 29, 2025
Raman spectroscopy, as a label-free optical technique, provides a unique solution for tissue diagnosis. However, due to the limitation of point-by-point acquisition mode and multivariate statistical analysis methods, conventional methods pose a major...
Deep learning based automated left atrial segmentation and flow quantification of real time phase contrast MRI in patients with atrial fibrillation.
The international journal of cardiovascular imaging
Apr 29, 2025
Real time 2D phase contrast (RTPC) MRI is useful for flow quantification in atrial fibrillation (AF) patients, but data analysis requires time-consuming anatomical contouring for many cardiac time frames. Our goal was to develop a convolutional neura...
Humans
Female
Blood Flow Velocity
Atrial Function, Left
Magnetic Resonance Imaging, Cine
Predictive Value of Tests
Atrial Fibrillation
Heart Atria
Heart Rate
Image Interpretation, Computer-Assisted
Observer Variation
Automation
Reproducibility of Results
Aged
Middle Aged
Male
Deep Learning
Time Factors
Magnetic Resonance Imaging
ConsisTNet: a spatio-temporal approach for consistent anatomical localization in endoscopic pituitary surgery.
International journal of computer assisted radiology and surgery
Apr 29, 2025
PURPOSE: Automated localization of critical anatomical structures in endoscopic pituitary surgery is crucial for enhancing patient safety and surgical outcomes. While deep learning models have shown promise in this task, their predictions often suffe...
Development and validation of a novel chronic pancreatitis pathological grade based on artificial intelligence.
Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
Apr 29, 2025
BACKGROUND: Effective chronic pancreatitis (CP) treatment requires accurate severity evaluation, but no histopathology grading system exists. This study aimed to develop and validate a novel CP pathological grade (Histopathology-derived CPpG) using q...
Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.
Journal of translational medicine
Apr 29, 2025
BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patients with epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma. However, not all patients with EGFR mutations respond to TKIs. This study...
Application of deep learning reconstruction combined with time-resolved post-processing method to improve image quality in CTA derived from low-dose cerebral CT perfusion data.
BMC medical imaging
Apr 29, 2025
BACKGROUND: To assess the effect of the combination of deep learning reconstruction (DLR) and time-resolved maximum intensity projection (tMIP) or time-resolved average (tAve) post-processing method on image quality of CTA derived from low-dose cereb...
Brain tumor detection empowered with ensemble deep learning approaches from MRI scan images.
Scientific reports
Apr 29, 2025
Brain tumor detection is essential for early diagnosis and successful treatment, both of which can significantly enhance patient outcomes. To evaluate brain MRI scans and categorize them into four types-pituitary, meningioma, glioma, and normal-this ...
Automated radiography assessment of ankle joint instability using deep learning.
Scientific reports
Apr 29, 2025
This study developed and evaluated a deep learning (DL)-based system for automatically measuring talar tilt and anterior talar translation on weight-bearing ankle radiographs, which are key parameters in diagnosing ankle joint instability. The system...
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