Three-dimensional textural and volumetric image analysis holds great potential in understanding the image data produced by multi-photon microscopy. In this paper, an algorithm that quantitatively analyzes the texture and the morphology of vasculature in engineered tissues is proposed. The investigated 3D artificial tissues consist of Human Umbilical Vein Endothelial Cells (HUVEC) embedded in co...

The prediction of induction chemotherapy response at the time of diagnosis may improve outcomes in osteosarcoma by allowing for personalized tailoring of therapy. The aim of this study was thus to investigate the predictive potential of the so far unexploited computational analysis of osteosarcoma magnetic resonance (MR) images. Fractal and gray level cooccurrence matrix (GLCM) algorithms were ...

This study presents a computer algorithm, which consists of four main steps (image acquisition, image pre-processing, nodule candidate detection, and feature extraction) for nodule detection in chest radiographs. Algorithm is applied on small-cell type of lung cancer (SCLC) and non-small-cell type of lung cancer (NSCLC) images. Total 50 images (25 from each category) were used to estimate geome...

This paper uses an analysis of Speeded up Robust Feature (SURF), based on the method of Linear Interpolation for camera distortion calibration, for high-density crowd counting. The eigenvalues are built on the Gray Level Co-occurrence Matrix (GLCM) features and the SURF features. Through the method of linear interpolation, weight values are interpolated to reduce the error, which is caused by c...

Mechanical properties of internal curing concrete are greatly affected by its physical such as water content, cementing material porosity, and saturation. At the micro- level, impact is finally reflected in surface texture materials. In this study, image recognition technology was used to find that samples have significant micromorphology features. A parameter–strength model established based o...

This study proposes a novel method for multichannel image gray level co-occurrence matrix (GLCM) texture representation. It is well known that the standard procedure for the automatic extraction of GLCM textures is based on a mono-spectral image. In real applications, however, the GLCM texture feature extraction always refers to multi/hyperspectral images. The widely used strategy to deal with ...

Monitoring of forests is important for the diagnosis insect damage to vegetation. Detection and monitoring damaged areas facilitates control pests practitioners. For this purpose, Unmanned Aerial Vehicles (UAVs) have been recently used detect areas. In order distinguish from healthy on UAV images, it necessary extract feature parameters images. Therefore, extraction an step in Computer Aided Di...

This paper proposed a novel voting ranking random forests (VRRF) method for solving hepatocellular carcinoma (HCC) image classification problem. Firstly, in preprocessing stage, this paper used bilateral filtering for hematoxylin-eosin (HE) pathological images. Next, this paper segmented the bilateral filtering processed image and got three different kinds of images, which include single binary...

Rapid and label-free imaging methods for accurate cell classification are highly desired for biology and clinical research. To improve consistency of classification performance, we have developed an approach of pattern analysis by gray level co-occurrence matrix (GLCM) algorithm to extract textural features at multiple pixel distances from cross-polarized diffraction image (p-DI) pairs, which w...

In this paper, a new method for heuristics and intermediate features based image retrieval is proposed. Heuristic features are identified and directly stored into the database and easily retrieved also. An algorithm is used to convert low level features hue, saturation and intensity in HSI space to semantic based color names. Images can be retrieved by these semantic color names. For semantics ...