- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
[IEEE 2019 IEEE International Conference on Electrical Engineering and Photonics (EExPolytech) - St. Petersburg, Russia (2019.10.17-2019.10.18)] 2019 IEEE International Conference on Electrical Engineering and Photonics (EExPolytech) - Radiomics: Extracting more Features using Endoscopic Imaging
摘要： Cancer is the leading cause of death in the world and delayed detection being the cause of the most significant factor for its high mortality rate. Computers can help radiologists in analyzing medical images and detection of cancer. Radiomics refers to the computerized extraction of information from medical images and provides the potential for making cancer screening with high rapid and more accurate using machine learning algorithms. Endoscopic imaging and X-ray imaging (Computed tomography) are two common methods used in medical imaging. In this paper, the advantages and limitations of endoscopic and CT scan images discussed. Then the features that can be extracted from endoscopic and CT scans are discussed and finally these two imaging methods are considered and compared to use for computer-aided detection systems.
关键词： feature extraction,Computed tomography (CT) scan,Endoscopic image,Radiomics,texture features
更新于2025-09-12 10:27:22
-
Endoscopic image enhancement with noise suppression
摘要： Stereoscopic endoscopes have been used increasingly in minimally invasive surgery to visualise the organ surface and manipulate various surgical tools. However, insuf?cient and irregular light sources become major challenges for endoscopic surgery. Not only do these conditions hinder image processing algorithms, sometimes surgical tools are barely visible when operating within low-light regions. In addition, low-light regions have low signal-to-noise ratio and metrication artefacts due to quantisation errors. As a result, present image enhancement methods usually suffer from heavy noise ampli?cation in low-light regions. In this Letter, the authors propose an effective method for endoscopic image enhancement by identifying different illumination regions and designing the enhancement design criteria for desired image quality. Compared with existing image enhancement methods, the proposed method is able to enhance the low-light region while preventing noise ampli?cation during image enhancement process. The proposed method is tested with 200 images acquired by endoscopic surgeries. Computed results show that the proposed algorithm can outperform state-of-the-art algorithms for image enhancement, in terms of naturalness image quality evaluator and illumination index.
关键词： image quality,endoscopic image enhancement,noise suppression,minimally invasive surgery,illumination regions
更新于2025-09-04 15:30:14