AI Medical Compendium Journal:
Journal of biophotonics

Showing 31 to 40 of 107 articles

Deep learning-based pigment analysis model trained with optical approach and ground truth assistance.

Journal of biophotonics
This study introduces an integrated training method combining the optical approach with ground truth for skin pigment analysis. Deep learning is increasingly applied to skin pigment analysis, primarily melanin and hemoglobin. While regression analysi...

Indocyanine green-based fluorescence imaging improved by deep learning.

Journal of biophotonics
Intraoperative identification of malignancies using indocyanine green (ICG)-based fluorescence imaging could provide real-time guidance for surgeons. Existing ICG-based fluorescence imaging mostly operates in the near-infrared (NIR)-I (700-1000 nm) o...

Deep learning analysis of mid-infrared microscopic imaging data for the diagnosis and classification of human lymphomas.

Journal of biophotonics
The present study presents an alternative analytical workflow that combines mid-infrared (MIR) microscopic imaging and deep learning to diagnose human lymphoma and differentiate between small and large cell lymphoma. We could show that using a deep l...

Imaging inside highly scattering media using hybrid deep learning and analytical algorithm.

Journal of biophotonics
Imaging through highly scattering media is a challenging problem with numerous applications in biomedical and remote-sensing fields. Existing methods that use analytical or deep learning tools are limited by simplified forward models or a requirement...

Deep-learning visualization enhancement method for optical coherence tomography angiography in dermatology.

Journal of biophotonics
Optical coherence tomography angiography (OCTA) in dermatology usually suffers from low image quality due to the highly scattering property of the skin, the complexity of cutaneous vasculature, and limited acquisition time. Deep-learning methods have...

Fourier ptychographic and deep learning using breast cancer histopathological image classification.

Journal of biophotonics
Automated, as well as accurate classification with breast cancer histological images, was crucial for medical applications because of detecting malignant tumors via histopathological images. In this work create a Fourier ptychographic (FP) and deep l...

Quantitative phase imaging of living red blood cells combining digital holographic microscopy and deep learning.

Journal of biophotonics
Digital holographic microscopy as a non-contacting, non-invasive, and highly accurate measurement technology, is becoming a valuable method for quantitatively investigating cells and tissues. Reconstruction of phases from a digital hologram is a key ...

Label-free histological analysis of retrieved thrombi in acute ischemic stroke using optical diffraction tomography and deep learning.

Journal of biophotonics
For patients with acute ischemic stroke, histological quantification of thrombus composition provides evidence for determining appropriate treatment. However, the traditional manual segmentation of stained thrombi is laborious and inconsistent. In th...

Rapid detection of cholecystitis by serum fluorescence spectroscopy combined with machine learning.

Journal of biophotonics
While cholecystitis is a critical public health problem, the conventional diagnostic methods for its detection are time consuming, expensive and insufficiently sensitive. This study examined the possibility of using serum fluorescence spectroscopy an...

Optical time-stretch imaging flow cytometry in the compressed domain.

Journal of biophotonics
Imaging flow cytometry based on optical time-stretch (OTS) imaging combined with a microfluidic chip attracts much attention in the large-scale single-cell analysis due to its high throughput, high precision, and label-free operation. Compressive sen...