AIMC Topic: Microscopy

Clear Filters Showing 11 to 20 of 617 articles

Deep learning model for early acute lymphoblastic leukemia detection using microscopic images.

Scientific reports
Cancer of bone marrow is classified as Acute Lymphoblastic Leukemia (ALL), an abnormal growth of lymphoid progenitor cells. It affects both children and adults and is the most predominant form of infantile cancer. Currently, there has been significan...

Adaptive-learning physics-assisted light-field microscopy enables day-long and millisecond-scale super-resolution imaging of 3D subcellular dynamics.

Nature communications
Long-term and high-spatiotemporal-resolution 3D imaging of living cells remains an unmet challenge for super-resolution microscopy, owing to the noticeable phototoxicity and limited scanning speed. While emerging light-field microscopy can mitigate t...

High-efficiency spatially guided learning network for lymphoblastic leukemia detection in bone marrow microscopy images.

Computers in biology and medicine
Leukemia is a hematologic tumor that proliferates in bone marrow and seriously affects the survival of patients. Early and accurate diagnosis is crucial for effective leukemia treatment. Traditional diagnostic methods rely on experts' subjective anal...

Development and validation of deep learning for predicting the growth of ovarian cancer organoids.

Chinese medical journal
BACKGROUND: Organoids have attracted enormous interest in disease modeling, drug screening, and precision medicine. However, developing robust patient-derived organoids (PDOs) was time-consuming, costly, and had low success rates for certain cancer t...

Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging.

Nature communications
The process of protein aggregation, central to neurodegenerative diseases like Huntington's, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in d...

Comparison of conventional and radiomics-based analysis of myocardial infarction using multimodal non-linear optical microscopy.

Scientific reports
Myocardial infarction, a leading cause of mortality worldwide, leaves survivors at significant risk of recurrence caused by scar-related re-entrant ventricular tachyarrhythmias. Effective treatment with ablation therapy requires a precise guidance sy...

Fusion of microscopic and diffraction images with VGG net for budding yeast recognition in imaging flow cytometry.

Scientific reports
Microscopic-Diffraction Imaging Flow Cytometry (MDIFC) is a high-throughput, stain-free technology that captures paired microscopic and diffraction images of cellular events, utilizing machine learning for the classification of cell subpopulations. H...

Deformable detection transformers for domain adaptable ultrasound localization microscopy with robustness to point spread function variations.

Scientific reports
Super-resolution imaging has emerged as a rapidly advancing field in diagnostic ultrasound. Ultrasound Localization Microscopy (ULM) achieves sub-wavelength precision in microvasculature imaging by tracking gas microbubbles (MBs) flowing through bloo...

Optical Resolution of the Morphological Change of Single Nanoparticles at Native Conditions: A Nonsuper-Resolution Approach.

ACS sensors
Label-free optical imaging of the morphology of single nanoparticles under native conditions remains a challenging task despite its importance in the synthesis, properties, and applications of nanomaterials. Here, we developed an angular scanning dar...

Deep learning-based automated detection and multiclass classification of soil-transmitted helminths and Schistosoma mansoni eggs in fecal smear images.

Scientific reports
In this work, we developed an automated system for the detection and classification of soil-transmitted helminths (STH) and Schistosoma (S.) mansoni eggs in microscopic images of fecal smears. We assembled an STH and S. mansoni dataset comprising ove...