<div style="text-align:justify;"> An image retrieval system was developed purposely to provide an efficient tool for a set of images from a collection of images in the large database that matches the u...<div style="text-align:justify;"> An image retrieval system was developed purposely to provide an efficient tool for a set of images from a collection of images in the large database that matches the user’s requirements in similarity evaluations such as image content similarity, edge, and colour similarity. Retrieving images based on the contents which are colour, texture, and shape is called content-based image retrieval (CBIR). This paper discusses and describes about the colour features technique for image retrieval systems. Several colour features technique and algorithms produced by the previous researcher are used to calculate the similarity between extracted features. This paper also describes about the specific technique about the colour basis features and combined features (hybrid techniques) between colour and shape features. </div>展开更多
Background A medical content-based image retrieval(CBIR)system is designed to retrieve images from large imaging repositories that are visually similar to a user′s query image.CBIR is widely used in evidence-based di...Background A medical content-based image retrieval(CBIR)system is designed to retrieve images from large imaging repositories that are visually similar to a user′s query image.CBIR is widely used in evidence-based diagnosis,teaching,and research.Although the retrieval accuracy has largely improved,there has been limited development toward visualizing important image features that indicate the similarity of retrieved images.Despite the prevalence of 3D volumetric data in medical imaging such as computed tomography(CT),current CBIR systems still rely on 2D cross-sectional views for the visualization of retrieved images.Such 2D visualization requires users to browse through the image stacks to confirm the similarity of the retrieved images and often involves mental reconstruction of 3D information,including the size,shape,and spatial relations of multiple structures.This process is time-consuming and reliant on users'experience.Methods In this study,we proposed an importance-aware 3D volume visualization method.The rendering parameters were automatically optimized to maximize the visibility of important structures that were detected and prioritized in the retrieval process.We then integrated the proposed visualization into a CBIR system,thereby complementing the 2D cross-sectional views for relevance feedback and further analyses.Results Our preliminary results demonstrate that 3D visualization can provide additional information using multimodal positron emission tomography and computed tomography(PETCT)images of a non-small cell lung cancer dataset.展开更多
The Albian-Maastrichtian interval of the Ivorian sedimentary basin has been the subject of numerous sedimentological, biostratigraphic, and geophysical studies. However, its geochemical characteristics remain relative...The Albian-Maastrichtian interval of the Ivorian sedimentary basin has been the subject of numerous sedimentological, biostratigraphic, and geophysical studies. However, its geochemical characteristics remain relatively unexplored. This study aims to determine the oil potential and the nature of the organic matter it contains. It focuses on the geochemical analysis (physicochemical method) of two oil wells located in the offshore sedimentary basin of Côte d’Ivoire, specifically in the Abidjan margin. A total of 154 cuttings samples from wells TMH-1X and TMH-2X were analyzed to determine their oil potential and the nature of the organic matter (OM) they contain. The analyses were performed using Rock-Eval pyrolysis, a method that characterizes the amount of hydrocarbons generated by the organic matter present in the rocks. The key parameters measured include Total Organic Carbon (TOC), Hydrogen Index (HI), oil potential (S2), and maximum pyrolysis temperature (Tmax). These parameters are used to assess the amount of organic matter, its thermal maturity, and its potential to generate hydrocarbons in the studied wells. The results show significant variations between different stratigraphic levels. In well TMH-1X, the Cenomanian and Campanian intervals stand out with very good quantities of organic matter (OM) with good oil potential, although often immature. In contrast, other stages such as the Albian and Turonian contain organic matter in moderate to low quantities, often immature and of continental type, which limits their capacity to generate hydrocarbons. In well TMH-2X, a similar trend is observed. Despite an abundance of organic matter, the oil potential remains low in most of the studied stages. The organic matter is primarily of type III (continental origin) and thermally immature, indicating a low potential for hydrocarbon generation. The study reveals that, although some intervals exhibit high-quality organic matter, the majority of the samples show insufficient maturity for effective hydrocarbon production. Wells TMH-1X and TMH-2X offer limited oil potential, requiring more advanced maturation conditions to fully exploit the hydrocarbon resources.展开更多
CBIR(Content Based Im age Retrieval)是当前多媒体检索的热点 .颜色特征是图像检索的重要特征 .为了提高颜色特征的检索效果 ,在提取图像主色特征的基础上 ,进一步提取了相应的主色空间分布信息——主色矩特征 ,并建立了图像主色特征...CBIR(Content Based Im age Retrieval)是当前多媒体检索的热点 .颜色特征是图像检索的重要特征 .为了提高颜色特征的检索效果 ,在提取图像主色特征的基础上 ,进一步提取了相应的主色空间分布信息——主色矩特征 ,并建立了图像主色特征的描述模型 .在改进加权二次型相似性度量方法的基础上 ,提出主色多特征相似性度量方法 ,并对几种不同的相似性度量方案进行了对比 ,其中 DCME方法在 WWW发布方式的 CBIR原型系统上取得了较好的实验结果 .展开更多
文摘<div style="text-align:justify;"> An image retrieval system was developed purposely to provide an efficient tool for a set of images from a collection of images in the large database that matches the user’s requirements in similarity evaluations such as image content similarity, edge, and colour similarity. Retrieving images based on the contents which are colour, texture, and shape is called content-based image retrieval (CBIR). This paper discusses and describes about the colour features technique for image retrieval systems. Several colour features technique and algorithms produced by the previous researcher are used to calculate the similarity between extracted features. This paper also describes about the specific technique about the colour basis features and combined features (hybrid techniques) between colour and shape features. </div>
文摘Background A medical content-based image retrieval(CBIR)system is designed to retrieve images from large imaging repositories that are visually similar to a user′s query image.CBIR is widely used in evidence-based diagnosis,teaching,and research.Although the retrieval accuracy has largely improved,there has been limited development toward visualizing important image features that indicate the similarity of retrieved images.Despite the prevalence of 3D volumetric data in medical imaging such as computed tomography(CT),current CBIR systems still rely on 2D cross-sectional views for the visualization of retrieved images.Such 2D visualization requires users to browse through the image stacks to confirm the similarity of the retrieved images and often involves mental reconstruction of 3D information,including the size,shape,and spatial relations of multiple structures.This process is time-consuming and reliant on users'experience.Methods In this study,we proposed an importance-aware 3D volume visualization method.The rendering parameters were automatically optimized to maximize the visibility of important structures that were detected and prioritized in the retrieval process.We then integrated the proposed visualization into a CBIR system,thereby complementing the 2D cross-sectional views for relevance feedback and further analyses.Results Our preliminary results demonstrate that 3D visualization can provide additional information using multimodal positron emission tomography and computed tomography(PETCT)images of a non-small cell lung cancer dataset.
文摘The Albian-Maastrichtian interval of the Ivorian sedimentary basin has been the subject of numerous sedimentological, biostratigraphic, and geophysical studies. However, its geochemical characteristics remain relatively unexplored. This study aims to determine the oil potential and the nature of the organic matter it contains. It focuses on the geochemical analysis (physicochemical method) of two oil wells located in the offshore sedimentary basin of Côte d’Ivoire, specifically in the Abidjan margin. A total of 154 cuttings samples from wells TMH-1X and TMH-2X were analyzed to determine their oil potential and the nature of the organic matter (OM) they contain. The analyses were performed using Rock-Eval pyrolysis, a method that characterizes the amount of hydrocarbons generated by the organic matter present in the rocks. The key parameters measured include Total Organic Carbon (TOC), Hydrogen Index (HI), oil potential (S2), and maximum pyrolysis temperature (Tmax). These parameters are used to assess the amount of organic matter, its thermal maturity, and its potential to generate hydrocarbons in the studied wells. The results show significant variations between different stratigraphic levels. In well TMH-1X, the Cenomanian and Campanian intervals stand out with very good quantities of organic matter (OM) with good oil potential, although often immature. In contrast, other stages such as the Albian and Turonian contain organic matter in moderate to low quantities, often immature and of continental type, which limits their capacity to generate hydrocarbons. In well TMH-2X, a similar trend is observed. Despite an abundance of organic matter, the oil potential remains low in most of the studied stages. The organic matter is primarily of type III (continental origin) and thermally immature, indicating a low potential for hydrocarbon generation. The study reveals that, although some intervals exhibit high-quality organic matter, the majority of the samples show insufficient maturity for effective hydrocarbon production. Wells TMH-1X and TMH-2X offer limited oil potential, requiring more advanced maturation conditions to fully exploit the hydrocarbon resources.
