AIMC Topic: Image Processing, Computer-Assisted

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Leveraging retinanet based object detection model for assisting visually impaired individuals with metaheuristic optimization algorithm.

Scientific reports
Visually impaired individuals suffer many problems in handling their everyday activities like road crossing, writing, finding an object, reading, and so on. However, many navigation methods are available, and efficient object detection (OD) methods f...

Distinct actin microfilament localization during early cell plate formation through deep learning-based image restoration.

Plant cell reports
Using deep learning-based image restoration, we achieved high-resolution 4D imaging with minimal photodamage, revealing distinct localization and suggesting Lifeact-RFP-labeled actin microfilaments play a role in initiating cell plate formation. Phra...

Deep learning approach based on a patch residual for pediatric supracondylar subtle fracture detection.

Biomolecules & biomedicine
Supracondylar humerus fractures in children are among the most common elbow fractures in pediatrics. However, their diagnosis can be particularly challenging due to the anatomical characteristics and imaging features of the pediatric skeleton. In rec...

Deep learning segmentation of periarterial and perivenous capillary-free zones in optical coherence tomography angiography.

Journal of biomedical optics
SIGNIFICANCE: Automated segmentation of periarterial and perivenous capillary-free zones (CFZs) in optical coherence tomography angiography (OCTA) can significantly improve early detection and monitoring of diabetic retinopathy (DR), a leading cause ...

Deep learning-assisted analysis of single-particle tracking for automated correlation between diffusion and function.

Nature methods
Subcellular diffusion in living systems reflects cellular processes and interactions. Recent advances in optical microscopy allow the tracking of this nanoscale diffusion of individual objects with unprecedented precision. However, the agnostic and a...

Enhancing efficient deep learning models with multimodal, multi-teacher insights for medical image segmentation.

Scientific reports
The rapid evolution of deep learning has dramatically enhanced the field of medical image segmentation, leading to the development of models with unprecedented accuracy in analyzing complex medical images. Deep learning-based segmentation holds signi...

Speckle pattern analysis with deep learning for low-cost stroke detection: a phantom-based feasibility study.

Journal of biomedical optics
SIGNIFICANCE: Stroke is a leading cause of disability worldwide, necessitating rapid and accurate diagnosis to limit irreversible brain damage. However, many advanced imaging modalities (computerized tomography, magnetic resonance imaging) remain ina...

Annotation-Free Whole-Slide Image Analysis Method to Assess Immune Infiltration in Colorectal Cancer.

JCO precision oncology
PURPOSE: Tumor-infiltrating lymphocytes (TILs) play a crucial role in host antitumor processes. High level of TILs is associated with better outcomes for patients. We aim to automatically quantify TILs without any nuclei annotation and further constr...

Synthetic Lung Ultrasound Data Generation Using Autoencoder With Generative Adversarial Network.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Class imbalance is a significant challenge in medical image analysis, particularly in lung ultrasound (LUS), where severe patterns are often underrepresented. Traditional oversampling techniques, which simply duplicate original data, have limited eff...

BentRay-NeRF: Bent-Ray Neural Radiance Fields for Robust Speed-of-Sound Imaging in Ultrasound Computed Tomography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Ultrasound computed tomography (USCT) is a promising technique for breast cancer detection because of its quantitative imaging capability of the speed of sound (SOS) of soft tissues and the fact that malignant breast lesions often have a higher SOS c...