AI Medical Compendium Journal:
Journal of biomedical optics

Showing 91 to 100 of 103 articles

GPU-based deep convolutional neural network for tomographic phase microscopy with ℓ1 fitting and regularization.

Journal of biomedical optics
Tomographic phase microscopy (TPM) is a unique imaging modality to measure the three-dimensional refractive index distribution of transparent and semitransparent samples. However, the requirement of the dense sampling in a large range of incident ang...

Automated classification of multiphoton microscopy images of ovarian tissue using deep learning.

Journal of biomedical optics
Histopathological image analysis of stained tissue slides is routinely used in tumor detection and classification. However, diagnosis requires a highly trained pathologist and can thus be time-consuming, labor-intensive, and potentially risk bias. He...

Context encoding enables machine learning-based quantitative photoacoustics.

Journal of biomedical optics
Real-time monitoring of functional tissue parameters, such as local blood oxygenation, based on optical imaging could provide groundbreaking advances in the diagnosis and interventional therapy of various diseases. Although photoacoustic (PA) imaging...

Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography.

Journal of biomedical optics
Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback sc...

Deep neural network-based bandwidth enhancement of photoacoustic data.

Journal of biomedical optics
Photoacoustic (PA) signals collected at the boundary of tissue are always band-limited. A deep neural network was proposed to enhance the bandwidth (BW) of the detected PA signal, thereby improving the quantitative accuracy of the reconstructed PA im...

Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer.

Journal of biomedical optics
Lung cancer is the most prevalent type of cancer and the leading cause of cancer-related deaths worldwide. Coherent anti-Stokes Raman scattering (CARS) is capable of providing cellular-level images and resolving pathologically related features on hum...

Hybrid piezoresistive-optical tactile sensor for simultaneous measurement of tissue stiffness and detection of tissue discontinuity in robot-assisted minimally invasive surgery.

Journal of biomedical optics
To compensate for the lack of touch during minimally invasive and robotic surgeries, tactile sensors are integrated with surgical instruments. Surgical tools with tactile sensors have been used mainly for distinguishing among different tissues and de...

Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging.

Journal of biomedical optics
Surgical cancer resection requires an accurate and timely diagnosis of the cancer margins in order to achieve successful patient remission. Hyperspectral imaging (HSI) has emerged as a useful, noncontact technique for acquiring spectral and optical p...

Automatic Gleason grading of prostate cancer using quantitative phase imaging and machine learning.

Journal of biomedical optics
We present an approach for automatic diagnosis of tissue biopsies. Our methodology consists of a quantitative phase imaging tissue scanner and machine learning algorithms to process these data. We illustrate the performance by automatic Gleason gradi...

Neural networks improve brain cancer detection with Raman spectroscopy in the presence of operating room light artifacts.

Journal of biomedical optics
Invasive brain cancer cells cannot be visualized during surgery and so they are often not removed. These residual cancer cells give rise to recurrences.