AIMC Topic: Photoacoustic Techniques

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Rapid cancer diagnosis using deep learning-powered label-free subcellular-resolution photoacoustic histology.

Science advances
Traditional hematoxylin and eosin staining in formalin-fixed paraffin-embedded sections, while essential for diagnostic pathology, is time-consuming, labor intensive, and prone to artifacts that can obscure critical histological details. Label-free u...

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...

Deep learning and radiomics integration of photoacoustic/ultrasound imaging for non-invasive prediction of luminal and non-luminal breast cancer subtypes.

Breast cancer research : BCR
PURPOSE: This study aimed to develop a Deep Learning Radiomics integrated model (DLRN), which combines photoacoustic/ultrasound(PA/US)imaging with clinical and radiomics features to distinguish between luminal and non-luminal BC in a preoperative set...

Photoacoustic-Integrated Multimodal Approach for Colorectal Cancer Diagnosis.

ACS biomaterials science & engineering
Colorectal cancer remains a major global health challenge, emphasizing the need for advanced diagnostic tools that enable early and accurate detection. Photoacoustic (PA) spectroscopy, a hybrid technique combining optical absorption with acoustic res...

A Synergistic Approach Using Photoacoustic Spectroscopy and AI-Based Image Analysis for Post-Harvest Quality Assessment of Conference Pears.

Molecules (Basel, Switzerland)
This study presents a non-invasive approach to monitoring post-harvest fruit quality by applying CO laser photoacoustic spectroscopy (COLPAS) to study the respiration of "Conference" pears from local and commercially stored (supermarket) sources. Con...

Deep learning aided determination of the optimal number of detectors for photoacoustic tomography.

Biomedical physics & engineering express
Photoacoustic tomography (PAT) is a non-destructive, non-ionizing, and rapidly expanding hybrid biomedical imaging technique, yet it faces challenges in obtaining clear images due to limited data from detectors or angles. As a result, the methodology...

Unrolled deep learning for breast cancer detection using limited-view photoacoustic tomography data.

Medical & biological engineering & computing
Photoacoustic tomography (PAT) has emerged as a promising imaging modality for breast cancer detection, offering unique advantages in visualizing tissue composition without ionizing radiation. However, limited-view scenarios in clinical settings pres...

Photoacoustic Imaging with Attention-Guided Deep Learning for Predicting Axillary Lymph Node Status in Breast Cancer.

Academic radiology
RATIONALE AND OBJECTIVES: Preoperative assessment of axillary lymph node (ALN) status is essential for breast cancer management. This study explores the use of photoacoustic (PA) imaging combined with attention-guided deep learning (DL) for precise p...

Deep proximal gradient network for absorption coefficient recovery in photoacoustic tomography.

Physics in medicine and biology
The optical absorption properties of biological tissues in photoacoustic (PA) tomography are typically quantified by inverting acoustic measurements. Conventional approaches to solving the inverse problem of forward optical models often involve itera...

Unsupervised inter-domain transformation for virtually stained high-resolution mid-infrared photoacoustic microscopy using explainable deep learning.

Nature communications
Mid-infrared photoacoustic microscopy can capture biochemical information without staining. However, the long mid-infrared optical wavelengths make the spatial resolution of photoacoustic microscopy significantly poorer than that of conventional conf...