AIMC Topic: Imaging, Three-Dimensional
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A 3D lightweight network with Roberts edge enhancement model (LR-Net) for brain tumor segmentation.
Scientific reports
Jun 5, 2025
In clinical medicine, a reliable and resource-friendly computer-aided diagnosis (CAD) method for brain tumor segmentation is essential to enhance diagnostic accuracy and therapeutic outcomes, particularly in regions with uneven healthcare resource di...
AI-powered segmentation of bifid mandibular canals using CBCT.
BMC oral health
Jun 4, 2025
OBJECTIVE: Accurate segmentation of the mandibular and bifid canals is crucial in dental implant planning to ensure safe implant placement, third molar extractions and other surgical interventions. The objective of this study is to develop and valida...
Digital removal of dermal denticle layer using geometric AI from 3D CT scans of shark craniofacial structures enhances anatomical precision.
Scientific reports
Jun 4, 2025
Craniofacial morphometrics in sharks provide crucial insights into evolutionary history, geographical variation, sexual dimorphism, and developmental patterns. However, the fragile cartilaginous nature of shark craniofacial skeleton poses significant...
Enhancing Lesion Detection in Inflammatory Myelopathies: A Deep Learning-Reconstructed Double Inversion Recovery MRI Approach.
AJNR. American journal of neuroradiology
Jun 3, 2025
BACKGROUND AND PURPOSE: The imaging of inflammatory myelopathies has advanced significantly across time, with MRI techniques playing a pivotal role in enhancing lesion detection. However, the impact of deep learning (DL)-based reconstruction on 3D do...
Automated landmark-based mid-sagittal plane: reliability for 3-dimensional mandibular asymmetry assessment on head CT scans.
Clinical oral investigations
May 26, 2025
OBJECTIVE: The determination of the mid-sagittal plane (MSP) on three-dimensional (3D) head imaging is key to the assessment of facial asymmetry. The aim of this study was to evaluate the reliability of an automated landmark-based MSP to quantify man...
Accuracy and time efficiency of deep learning-based three-dimensional crown segmentation on intraoral scanning: a systematic review and meta-analysis.
Journal of dentistry
May 23, 2025
OBJECTIVES: Clinically, accurate tooth segmentation in intraoral scans is vital for clinical diagnosis and treatments. Deep learning is utilized for image segmentation in mesh segmentation such as intraoral scans lately. This review and meta-analysis...
Revealing 3D microanatomical structures of unlabeled thick cancer tissues using holotomography and virtual H&E staining.
Nature communications
May 22, 2025
In histopathology, acquiring subcellular-level three-dimensional (3D) tissue structures efficiently and without damaging the tissues during serial sectioning and staining remains a formidable challenge. We address this by integrating holotomography w...
SLIMBRAIN database: A multimodal image database of in vivo human brains for tumour detection.
Scientific data
May 21, 2025
Hyperspectral imaging (HSI) and machine learning (ML) have been employed in the medical field for classifying highly infiltrative brain tumours. Although existing HSI databases of in vivo human brains are available, they present two main deficiencies...
Semiautomated segmentation of breast tumor on automatic breast ultrasound image using a large-scale model with customized modules.
Scientific reports
May 19, 2025
To verify the capability of the Segment Anything Model for medical images in 3D (SAM-Med3D), tailored with low-rank adaptation (LoRA) strategies, in segmenting breast tumors in Automated Breast Ultrasound (ABUS) images. This retrospective study colle...
3D Micro-Expression Recognition Based on Adaptive Dynamic Vision.
Sensors (Basel, Switzerland)
May 18, 2025
In the research on intelligent perception, dynamic emotion recognition has been the focus in recent years. Small samples and unbalanced data are the main reasons for the low recognition accuracy of current technologies. Inspired by circular convoluti...
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