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Related Concept Videos

X-ray Imaging01:24

X-ray Imaging

German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with X-rays, and by 1900, X-ray was widely...
Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been developed.
Confocal Fluorescence Microscopy01:16

Confocal Fluorescence Microscopy

Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...
Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...

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Related Experiment Video

Updated: Jul 1, 2026

Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment
07:12

Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment

Published on: January 6, 2026

Semi-supervised YOLO-DEP for high-resolution X-ray component localization and counting.

Zhixuan Xiao1,2, Huahai Sun1,2, Xu Tuo1,2

  • 1Department of Engineering Physics, Tsinghua University, Beijing 100084, China.

Journal of X-Ray Science and Technology
|June 30, 2026
PubMed
Summary

This study introduces YOLO-DEP, a semi-supervised framework for accurately locating and counting tiny electronic components in X-ray images. It significantly reduces annotation needs while improving detection performance for industrial quality control.

Keywords:
X-ray imagingconvolutional neural networkobject countingsemi-supervised learning

Related Experiment Videos

Last Updated: Jul 1, 2026

Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment
07:12

Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment

Published on: January 6, 2026

Area of Science:

  • * Nuclear science and radiation imaging.
  • * Industrial quality control and automated inspection.

Background:

  • * Accurate localization and counting of small electronic components in high-resolution X-ray images is crucial but challenging.
  • * Traditional methods struggle with cluttered scenes, and deep learning methods require extensive annotated data.
  • * Existing approaches are limited in handling dense, small targets in complex industrial settings.

Purpose of the Study:

  • * To develop a semi-supervised object detection framework for high-precision localization and counting of tiny electronic components in large X-ray images.
  • * To reduce manual annotation costs by utilizing a novel semi-supervised label propagation strategy.
  • * To introduce a new large-scale dataset, LEEC, for X-ray electronic component counting.

Main Methods:

  • * Proposed YOLO-DEP, a novel object detector combining YOLOv11 with a Deep Encoding Processor (DEP) and Graph Attention Network (GAT).
  • * DEP module employs half-channel and spatial attention for enhanced feature discrimination of small, dense targets.
  • * Developed a semi-supervised label propagation strategy using feature similarity graphs and GAT for pseudo-label generation from minimal annotations.

Main Results:

  • * YOLO-DEP demonstrated superior performance compared to state-of-the-art detectors on the LEEC and DOTAv1 datasets.
  • * YOLO-DEP-x achieved 79.2% mAP50 and 70.9% mAP50-95 on the LEEC dataset.
  • * Achieved a low counting error rate of 0.8%, indicating high accuracy in component counting.

Conclusions:

  • * The proposed YOLO-DEP framework offers an effective solution for accurate electronic component localization and counting in high-resolution X-ray images.
  • * The semi-supervised approach significantly reduces annotation effort, making it practical for real-world applications.
  • * YOLO-DEP provides a deployable solution for industrial automation, nuclear inspection, and quality control.