Accurate colorectal lesion classification is important for computer-aided colonoscopy, yet many existing approaches require computationally intensive architectures. This study proposed and experimentally evaluated LHRF, which integrates BoVW encoding...
Women with suspected ischemic heart disease remain underrecognized, underdiagnosed, and undertreated, in part because conventional diagnostic pathways emphasize obstructive epicardial coronary disease and insufficiently account for life-stage-depende...
Multi-view industrial robot scanning requires efficient reconstruction of large point clouds while controlling onboard memory use and maintaining geometric and stitching quality. This paper presents a pairwise-cascade distributed reconstruction frame...
Noninvasive prediction of 1p/19q codeletion and isocitrate dehydrogenase (IDH) mutation may support preoperative assessment of lower-grade gliomas. We evaluated leakage-aware probability-level fusion of meta-information and multimodal radiomics. This...
Infrared imaging techniques are capable of providing reliable visual information across varying lighting conditions, particularly in environments with low or no illumination. However, traditional infrared image generation methods still face limitatio...
Coronary computed tomography angiography (CTCA) is established as a first-line investigation for suspected coronary artery disease and is increasingly used for anatomical, functional, and structural cardiac assessment. Fractal analysis (FA) provides...
Breast magnetic resonance imaging (MRI) offers three-dimensional anatomical information for reconstruction-oriented analysis, but annotated public datasets targeting implant-based reconstruction are limited. ImageBR contains MRI volumes from 44 patie...
This study aims to improve quantitative precipitation estimation at high spatial and temporal resolutions using Meteosat Second Generation (MSG) satellite imagery. In this context, two complementary models are exploited for the classification of prec...
Fire detection in low-resolution surveillance videos at night is challenging under poor illumination. Conventional methods rely on colour information or computationally intensive deep-learning models, potentially limiting their suitability for graysc...
Low-light image enhancement (LLIE) is a fundamental yet challenging task due to the presence of noise, loss of detail, and poor contrast in images captured under insufficient lighting conditions. Recent methods often rely solely on pixel-level transf...
Zero-shot image style transfer has recently attracted increasing attention, as it enables style manipulation without additional model optimization or parameter tuning. However, most existing approaches still rely on latent inversion, where introduced...
Corneal confocal microscopy (CCM), also referred to as in vivo confocal microscopy, is a non-invasive ophthalmic imaging technique that allows real-time visualization of the sub-basal nerve plexus and epithelial dendritic cells in the living cornea....
YOLO-GRAT integrates P3 Cross-Modal Gated Residual Fusion with adaptively weighted Triplet Attention inside backbone C3 bottlenecks of a YOLOv5-based visible–infrared detector. The fusion block combines input-dependent modality mixing, a mean-r...
In 3D computed tomography segmentation, differences in voxel spacing mean that equal separations on the voxel grid correspond to different physical distances. Many Transformers incorporate positional encodings because self-attention does not explicit...
Genicular artery embolization (GAE) has emerged as a minimally invasive treatment for symptomatic knee osteoarthritis, but the evolution of its clinical evidence base remains incompletely characterized. This study evaluated the development of GAE res...
Public brain metastasis MRI cohorts are widely used for prognostic modeling, but whether an endpoint is identifiable at the available sample size is rarely tested. We evaluated eight clinical endpoints in two public cohorts, Yale/BraTS-MET (199 patie...
Chest radiographs come with abundant free-text reports but scarce lesion-level annotation, so report text increasingly supervises localization. This structured narrative review, written for model developers, benchmark curators, and evaluators of clin...
Retinal vessel segmentation remains difficult along thin, low-contrast branches. We evaluate a conditional diffusion refiner for probability maps from a lightweight U-Net with reverse attention (LU-Net+RA). A frozen mask autoencoder produces a spatia...
Autonomous vehicles need fast, reliable perception to detect vehicles, pedestrians, cyclists, traffic signs, and other road objects in real time. This paper surveys camera-based one-stage object detectors for autonomous driving. It traces 24 one-stag...
We extend our previous study on extended 5-channel images, which add two pseudo-invisible-light channels, estimated by spectral reconstruction (MST++) and polynomial extrapolation, to the RGB channels. We first ask whether the accuracy gain reflects...
Registration techniques play a critical role in computer vision and medical image analysis, enabling the alignment of images acquired at different times or from different modalities. The increasing demand for high-resolution and real-time processing...
Graf-method ultrasound supports early assessment of developmental dysplasia of the hip (DDH). This study assessed a sequential artificial-intelligence-assisted workflow and clinicians’ Checklist I decisions with and without computer-aided diagn...
Watermark exclusion masks are often evaluated with reference annotations, although image issuance requires a mask that can be generated without them. We measured the difference on 27 IDRiD test fundus images using a sidecar-dependent block-DCT waterm...
Underwater robotics platforms are equipped with onboard cameras for navigation and mapping within deep-sea environments, either assisted by an operator in human-in-the-loop missions or automatically through real-time processing of live video. The imp...
Video anomaly detection (VAD) has evolved from handcrafted feature-based methods to deep learning and foundation model-based approaches, enabling improved detection of complex and previously unseen events. This review examines this evolution through...
Existing computed tomography (CT) fracture-risk models typically output one scalar score per vertebra without localising the predicted change. We built and internally validated a three-dimensional (3D) convolutional network forecasting, from one base...
Concept Bottleneck Models (CBMs) route predictions through a layer of human-understandable concepts, but classical CBMs need a concept label for every training image, a cost that is high in medicine. Vision–language models (VLMs) remove that re...
Low-level vision pipelines often evaluate local operators densely, including homogeneous regions that contribute weak responses. We introduce VarSelect, a deterministic, training-free selective-computation framework that decouples constant-time local...
Nondestructive estimation of pigment content and chlorophyll fluorescence traits is valuable for vertical farming. However, hyperspectral models for fluorescence traits have rarely been tested on vertically farmed crops. This study evaluated a VNIR h...
Accurate 3D medical image segmentation requires effective integration of encoder details and decoder semantics. However, their relative contributions vary across decoding stages and spatial locations, and attention based only on the current feature p...
Limited annotation and class imbalance remain important challenges in medical image analysis. SSGNet++ examines class-specific StyleGAN3 augmentation for classification and an iterative pseudo-labelling pipeline for segmentation, combining prediction...
Thermal drones help to search for missing people in the wilderness, but flying high enough to cover wide areas shrinks each person to just a few pixels, causing standard detectors to miss them. We introduce MicroSlicer, a lightweight method that impr...
Underwater marine debris detection remains challenging because light attenuation, scattering, low contrast, blurred object boundaries, and complex seabed backgrounds degrade feature representation and hinder the reliable detection of small, sparsely...
The attitude determination accuracy of star sensors depends heavily on the precision of star centroid estimation. However, complex degradation scenarios—including low signal-to-noise ratio (SNR), intense stray light, and isolated hot pixels ind...
Accurate detection and counting of Gobiocypris rarus larvae are essential for laboratory toxicological experiments and aquatic biological research. However, the larvae detection task remains challenging due to small object size, dense aggregation, ra...
Low-field magnetic resonance imaging includes portable and open architectures, but quantitative results remain sensitive to field strength, temperature, environment, system state, acquisition, reconstruction, and model fitting. This methodological re...
Unsupervised clustering of deep image features is often proposed for unlabeled image archives, yet it is usually judged by internal criteria rather than by agreement with expert annotations. In a single domain of texture images, namely full-size rock...
Square fiducial markers provide a robust and efficient way to establish visual references in camera localization tasks, combining reliable detection with unique identification through an embedded binary code. The robustness of these systems depends l...
Breast dynamic contrast-enhanced MRI acquires one image volume before contrast injection and several after it; each volume is a contrast phase. Which phases a tumour segmentation model needs has not been systematically tested. In 980 examinations fro...
The journal retracts the article titled “A Feature Extraction Using Probabilistic Neural Network and BTFSC-Net Model with Deep Learning for Brain Tumor Classification” [...]
Manual sinus magnetic resonance imaging (MRI) annotations are valuable but difficult to scale. We evaluated PARASIDE, an nnU-Net-based framework for automated sinus compartment segmentation on T1-weighted MRI, against historical manual annotations an...
Preclinical imaging in animal models of human disease is advancing rapidly, driven by developments in instrumentation, technology, and comparative medicine [...]
Multi-sequence MRI is the standard for glioma assessment, but complete or contrast-enhanced protocols are not always available (withheld gadolinium, low-field MRI, incomplete archives). We asked whether tumor localization improves grade classificatio...
Object detection is pivotal for automated industrial surface defect detection. However, industrial imaging of metal surfaces is often hampered by adverse factors such as uneven illumination, strong specular reflection, low contrast, and blurring of t...
Virtual reality–based subjective visual vertical (VR-SVV) testing is a portable method for assessing verticality perception relative to gravity, but its protocols remain inconsistent. This scoping review examined the basic VR-SVV outcomes, reli...
In this study, we investigated the transfer of a previously established LED-based Geant4 optical-photon simulation framework to experimental bioluminescence imaging (BLI) using two commercial imaging systems. An IVIS 200 and a SmART+ BLI/CT system we...
Small-scale objects and partially occluded targets in complex traffic scenarios impose significant challenges on the feature representation capability of target detection models, while the increasing computational burden limits detection efficiency....
Accurate segmentation of oral mucosal lesions remains challenging because lesion regions often resemble surrounding mucosa, with subtle color differences, weak texture contrast, unclear boundaries, and distractors such as saliva, folds, reflections,...
Although numerous studies have developed promising diagnostic algorithms, many have yet to be translated into workflow-integrated tools. Gliomas represent a substantial proportion of primary brain tumors, and their preoperative differentiation by tum...
Underwater vision technology serves as the core foundation for enabling “perception and interaction” in intelligent underwater robotic systems; however, its performance is severely constrained by image degradation. This paper provides a n...
