AIMC Topic: Imaging, Three-Dimensional

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Multiphoton microscopy and tissue clearing for 3D characterization of the vasculature and fibrosis remodeling in rat dystrophic skeletal muscle.

Scientific reports
Duchenne muscular dystrophy (DMD) is characterized by progressive muscle fiber degeneration and replacement by fibrous and adipose tissues, alongside significant vascular abnormalities. Traditional two-dimensional (2D) histological assessments provid...

AI-driven 3D CT imaging prediction model for improving preoperative detection of visceral pleural invasion in early-stage lung cancer.

PloS one
Visceral pleural invasion (VPI) is a critical prognostic factor in early-stage non-small-cell lung cancer (NSCLC), significantly affecting patient outcomes. Conventional computed tomography (CT) often fails to diagnose VPI accurately. This retrospect...

Efficient hybrid fuzzy weighted 3D FCNN with TSO PSO optimization for accurate multi modal MRI brain tumor classification.

Scientific reports
Detecting and segmenting brain tumors from 3D MRI images is a challenging and time-intensive task for clinicians. This research introduces an innovative hybrid architecture for deep learning, comprising a 3D fully convolutional neural network (3D-FCN...

Deep learning-enhanced 3D real-time photoacoustic imaging using experimental ground truths obtained from fluctuation imaging.

Physics in medicine and biology
3D conventional photoacoustic (PA) imaging often suffers from visibility artifacts caused by the limited bandwidth and constrained viewing angles of ultrasound transducers, as well as the use of sparse arrays. PA fluctuation imaging (PAFI), which lev...

Towards Robust Brain Midline Shift Detection: A YOLO-Based 3D Slicer Extension with a Novel Dataset.

Neuroinformatics
Accurate detection of brain midline shift is critical for the diagnosis and monitoring of neurological conditions such as traumatic brain injuries, strokes, and tumors. This study aims to address the lack of dedicated datasets and tools for this task...

Deep learning detection of dynamic exocytosis events in fluorescence TIRF microscopy.

PLoS computational biology
Segmentation and detection of biological objects in fluorescence microscopy is of paramount importance in cell imaging. Deep learning approaches have recently shown promise to advance, automatize and accelerate analysis. However, most of the interest...

AI-based modality-agnostic classification system for vascular calcifications.

Scientific reports
The importance of vascular calcification in major adverse cardiovascular events such as heart attacks or strokes has been established. However, calcifications have heterogeneous phenotypes, and their influence on diseased tissue stability remains poo...

cryoTIGER: deep-learning based tilt interpolation generator for enhanced reconstruction in cryo electron tomography.

Communications biology
Cryo-electron tomography enables the visualization of macromolecular complexes within native cellular environments but is limited by incomplete angular sampling and the maximal electron dose that biological specimens can be exposed to. Here, we devel...

Automatic segmentation of male pelvic floor soft tissue structures for anatomical simulation and morphological assessment in lower rectal cancer surgery.

Techniques in coloproctology
BACKGROUND: Pelvic anatomy is a complex network of organs that varies between individuals. Understanding the anatomy of individual patients is crucial for precise rectal cancer surgeries. Therefore, developing technology that can allow visualization ...

HCS-3DX, a next-generation AI-driven automated 3D-oid high-content screening system.

Nature communications
Self-organised three-dimensional (3D) cell cultures, collectively called 3D-oids, include spheroids, organoids and other co-culture models. Systematic evaluation of these models forms a critical new generation of high-content screening (HCS) systems ...