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Omnidirectional images (ODIs) are commonly used in real-world visual tasks, and high-resolution ODIs help improve the performance of related visual tasks. Most existing super-resolution methods for ODIs use end-to-end learning strategies,…
Purpose. Localizing structures and estimating the motion of a specific target region are common problems for navigation during surgical interventions. Optical coherence tomography (OCT) is an imaging modality with a high spatial and…
High anisotropy in volumetric medical images can lead to the inconsistent quantification of anatomical and pathological structures. Particularly in optical coherence tomography (OCT), slice spacing can substantially vary across and within…
Deep learning-based hyperspectral image (HSI) classification and object detection techniques have gained significant attention due to their vital role in image content analysis, interpretation, and wider HSI applications. However, current…
Intravascular polarimetry with catheter-based polarization-sensitive optical coherence tomography (PS-OCT) complements the high-resolution structural tomograms of OCT with morphological contrast available through polarimetry. Its clinical…
To achieve a distributed reflectivity measurement along an optical fiber, we develop a simplified cost-effective configuration of optical correlation- (or coherence-) domain reflectometry based on a synthesized optical coherence function by…
A neural-network (NN)-based method for high-speed, high-definition dynamic optical coherence tomography (DOCT) using full-field swept-source optical coherence microscopy (FF-SS-OCM) is demonstrated. FF-SS-OCM provides high-definition OCT…
Optical diffraction tomography (ODT) has emerged as an important label-free tool in biomedicine to measure the three-dimensional (3D) structure of a biological sample. In this paper, we describe ODT using second-harmonic generation (SHG)…
Shape tracking of medical devices using strain sensing properties in optical fibers has seen increased attention in recent years. In this paper, we propose a novel guidance system for intra-arterial procedures using a distributed strain…
Out-of-distribution (OOD) detection ensures safe and reliable model deployment. Contemporary OOD algorithms using geometry projection can detect OOD or adversarial samples from clean in-distribution (ID) samples. However, this setting…
Open-vocabulary object detection (OVOD) aims to detect known and unknown objects in the open world by leveraging text prompts. Benefiting from the emergence of large-scale vision--language pre-trained models, OVOD has demonstrated strong…
Optical coherence tomography (OCT) is a prevalent imaging technique for retina. However, it is affected by multiplicative speckle noise that can degrade the visibility of essential anatomical structures, including blood vessels and tissue…
Optical coherence tomography (OCT) is an important interferometric diagnostic technique which provides cross-sectional views of the subsurface microstructure of biological tissues. However, the imaging quality of high-speed OCT is limited…
Image Copy Detection (ICD) aims to identify manipulated content between image pairs through robust feature representation learning. While self-supervised learning (SSL) has advanced ICD systems, existing view-level contrastive methods…
In the maintenance of optical fiber networks, there is a growing demand for high-precision measurement of optical loss distribution and fault locations over long distances. In this study, we propose an OCDR method incorporating periodic…
Retinal neovascularization (RNV) is a vision threatening development in diabetic retinopathy (DR). Vision loss associated with RNV is preventable with timely intervention, making RNV clinical screening and monitoring a priority. Optical…
Nonuniform rotational distortion (NURD) correction is vital for endoscopic optical coherence tomography (OCT) imaging and its functional extensions, such as angiography and elastography. Current NURD correction methods require…
Clustering is a fundamental task in the computer vision and machine learning community. Although various methods have been proposed, the performance of existing approaches drops dramatically when handling incomplete high-dimensional data…
Optical coherence tomography (OCT) imaging is a well-known technology for visualizing retinal layers and helps ophthalmologists to detect possible diseases. Accurate and early diagnosis of common retinal diseases can prevent the patients…
In this paper, we extend the standard belief propagation (BP) sequential technique proposed in the tree-reweighted sequential method to the fully connected CRF models with the geodesic distance affinity. The proposed method has been applied…