Biomedical Optics Express

The mammalian oviduct (or fallopian tube) is a tubular organ hosting reproductive events leading to pregnancy. Dynamic 3D imaging of the mouse oviduct with optical coherence tomography (OCT) has recently emerged as a promising approach to study the hidden processes vital to elucidate the role of oviduct in mammalian reproduction and reproductive disorders. In particular, with an intravital window, in vivo OCT imaging is a powerful solution to studying how the oviduct transports preimplantation embryos towards the uterus for pregnancy, a long-standing question that is critical for uncovering the functional cause of tubal ectopic pregnancy...

Optical coherence tomography (OCT) is an ideal imaging technique for noninvasive and longitudinal monitoring of multicellular tumor spheroids (MCTS). However, the internal structure features within MCTS from OCT images are still not fully utilized. In this study, we developed cross-statistical, cross-screening, and composite-hyperparameter feature processing methods in conjunction with 12 machine learning models to assess changes within the MCTS internal structure. Our results indicated that the effective features combined with supervised learning models successfully classify OVCAR-8 MCTS culturing with 5,000 and 50,000 cell numbers, MCTS with pancreatic tumor cells (Panc02-H7) culturing with the ratio of 0%, 33%, 50%, and 67% of fibroblasts, and OVCAR-4 MCTS treated by 2-methoxyestradiol, AZD1208, and R-ketorolac with concentrations of 1, 10, and 25 µM...

Pulse oximetry represents a ubiquitous clinical application of optics in modern medicine. Recent studies have raised concerns regarding the potential impact of confounders, such as variable skin pigmentation and perfusion, on blood oxygen saturation measurement accuracy in pulse oximeters. Tissue-mimicking phantom testing offers a low-cost, well-controlled solution for characterizing device performance and studying potential error sources, which may thus reduce the need for costly in vivo trials. The purpose of this study was to develop realistic phantom-based test methods for pulse oximetry...

Many promising biomedical applications have been proposed for terahertz (THz) spectroscopy and diagnostic imaging techniques. Polarimetric imaging systems are generally useful for enhancing imaging contrasts, yet the interplay between THz polarization changes and the random discrete structures in biological samples is not well understood. In this work, we performed Monte Carlo simulations of the propagation of polarized THz waves in skin and adipose tissues based on the Mie scattering from intrinsic structures, such as hair follicles or sweat glands...

Anastomosis is a common and critical part of reconstructive procedures within gastrointestinal, urologic, and gynecologic surgery. The use of autonomous surgical robots such as the smart tissue autonomous robot (STAR) system demonstrates an improved efficiency and consistency of the laparoscopic small bowel anastomosis over the current da Vinci surgical system. However, the STAR workflow requires auxiliary manual monitoring during the suturing procedure to avoid missed or wrong stitches. To eliminate this monitoring task from the operators, we integrated an optical coherence tomography (OCT) fiber sensor with the suture tool and developed an automatic tissue classification algorithm for detecting missed or wrong stitches in real time...

Three-dimensional stacks acquired with confocal or two-photon microscopy are crucial for studying neuroanatomy. However, high-resolution image stacks acquired at multiple depths are time-consuming and susceptible to photobleaching. In vivo microscopy is further prone to motion artifacts. In this work, we suggest that deep neural networks with sine activation functions encoding implicit neural representations (SIRENs) are suitable for predicting intermediate planes and correcting motion artifacts, addressing the aforementioned shortcomings...

Automatic and precise polyp segmentation in colonoscopy images is highly valuable for diagnosis at an early stage and surgery of colorectal cancer. Nevertheless, it still posed a major challenge due to variations in the size and intricate morphological characteristics of polyps coupled with the indistinct demarcation between polyps and mucosas. To alleviate these challenges, we proposed an improved dual-aggregation polyp segmentation network, dubbed Dua-PSNet, for automatic and accurate full-size polyp prediction by combining both the transformer branch and a fully convolutional network (FCN) branch in a parallel style...

Hypertension is typically manifested as a latent symptom that requires detection through specialized equipment. This poses an inconvenience for individuals who need to undergo long-term blood pressure monitoring in their daily lives. Therefore, there is a need for a portable, non-contact method for estimating blood pressure. However, current non-contact blood pressure estimation methods often rely on relatively narrow datasets, lacking a broad range of blood pressure distributions. Additionally, their applicability is confined to controlled experimental environments...

In recent years, imaging photoplethysmograph (iPPG) pulse signals have been widely used in the research of non-contact blood pressure (BP) estimation, in which BP estimation based on pulse features is the main research direction. Pulse features are directly related to the shape of pulse signals while iPPG pulse signals are easily disturbed during the extraction process. To mitigate the impact of pulse feature distortion on BP estimation, it is necessary to eliminate interference while retaining valuable shape details in the iPPG pulse signal...

Slide-free imaging techniques have shown great promise in improving the histological workflow. For example, computational high-throughput autofluorescence microscopy by pattern illumination (CHAMP) has achieved high resolution with a long depth of field, which, however, requires a costly ultraviolet laser. Here, simply using a low-cost light-emitting diode (LED), we propose a deep learning-assisted framework of enhanced widefield microscopy, termed EW-LED, to generate results similar to CHAMP (the learning target)...

Both cataracts and age-related macular degeneration (AMD) may occur with aging and are often developed simultaneously. We performed a study to better characterize the impact of induced scatter on the quality of vision in the near periphery, a region where individuals with AMD typically maintain their functional vision. We used an optical instrument as a cataract simulator based on projecting at the eye's pupil plane phase masks with controlled spatial properties generated with a spatial light modulator. The phase wavefronts were designed to accurately replicate the angular distribution of light intensity in the retina found in cataractous eyes with different severities...

Identification of tumour margins during resection of the brain is critical for improving the post-operative outcomes. Due to the highly infiltrative nature of glioblastoma multiforme (GBM) and limited intraoperative visualization of the tumour margin, incomplete surgical resection has been observed to occur in up to 80 % of GBM cases, leading to nearly universal tumour recurrence and overall poor prognosis of 14.6 months median survival. This research presents a miniaturized, SiPMT-based optical system for simultaneous measurement of powerful DRS and weak auto-fluorescence for brain tumour detection...

Central venous pressure is an estimate of right atrial pressure and is often used to assess hemodynamic status. However, since it is measured invasively, non-invasive alternatives would be of great utility. The aim of this preliminary study was a) to investigate whether photoplethysmography (PPG) can be used to characterize venous system fluid motion and b) to find the model for venous blood volume modulations. For this purpose, we monitored the internal jugular veins using contact (cPPG) and video PPG during clinically validated physiological tests: abdominojugular test (AJT) and breath holding (BH)...

To alleviate the ill-posedness of diffuse fluorescence tomography (DFT) reconstruction and improve imaging quality and speed, a model-derived deep-learning method is proposed by combining extended Kalman filtering (EKF) with a long short term memory (LSTM) neural network, where the iterative process parameters acquired by implementing semi-iteration EKF (SEKF) served as inputs to the LSTM neural network correction model for predicting the optimal fluorescence distributions. To verify the effectiveness of the SEKF-LSTM algorithm, a series of numerical simulations, phantom and in vivo experiments are conducted, and the experimental results are quantitatively evaluated and compared with the traditional EKF algorithm...

We present the fabrication and implementation of low-cost optical quality 3D printed lenses, and their application as microscope objectives with different prescriptions. The imaging performance of the 3D printed lenses was benchmarked against commercially available optics including a 20 mm focal length 12.7 mm diameter NBK-7 plano-convex lens used as a low magnification objective, and a separate high magnification objective featuring three 6 mm diameter NBK-7 lenses with different positive and negative focal lengths...

Comprehensive visualization and accurate extraction of tumor vasculature are essential to study the nature of glioma. Nowadays, tissue clearing technology enables 3D visualization of human glioma vasculature at micron resolution, but current vessel extraction schemes cannot well cope with the extraction of complex tumor vessels with high disruption and irregularity under realistic conditions. Here, we developed a framework, FineVess, based on deep learning to automatically extract glioma vessels in confocal microscope images of cleared human tumor tissues...

For the effectiveness of a computer-aided diagnosis system, the quality of whole-slide image (WSI) is the foundation, and a useful autofocus method is an important part of ensuring the quality of WSI. The existing autofocus methods need to balance focusing speed and focusing accuracy, and need to be optimized separately for different samples or scenes. In this paper, a robust autofocus method based on fiber bundle illumination and image normalization analysis is proposed. For various application scenes, it meets the requirements of autofocusing through active illumination, such as bright field imaging and fluorescence imaging...

In neurosurgery, accurately identifying brain tumor tissue is vital for reducing recurrence. Current imaging techniques have limitations, prompting the exploration of alternative methods. This study validated a binary hierarchical classification of brain tissues: normal tissue, primary central nervous system lymphoma (PCNSL), high-grade glioma (HGG), and low-grade glioma (LGG) using transfer learning. Tumor specimens were measured with optical coherence tomography (OCT), and a MobileNetV2 pre-trained model was employed for classification...

The development of efficient genetically encoded indicators and actuators has opened up the possibility of reading and manipulating neuronal activity in living tissues with light. To achieve precise and reconfigurable targeting of large numbers of neurons with single-cell resolution within arbitrary volumes, different groups have recently developed all-optical strategies based on two-photon excitation and spatio-temporal shaping of ultrashort laser pulses. However, such techniques are often complex to set up and typically operate at a single wavelength only...

A multi-function sensor based on an all-dielectric metastructure for temperature and refractive index sensing simultaneously is designed and analyzed in this paper. The structure is composed of a periodic array of silicon dimers placed on the silicon dioxide substrate. By breaking the symmetry of the structure, the ideal bound states in the continuum can be converted to the quasi-bound states in the continuum, and three Fano resonances are excited in the near-infrared wavelength. Combining with the electromagnetic field distributions, the resonant modes of three Fano resonances are analyzed as magnetic dipole, magnetic toroidal dipole, and electric toroidal dipole, respectively...