scholarly journals Consolidated morphology

2006 ◽  
Author(s):  
Gaetan Lehmann ◽  
Richard Beare
Keyword(s):  
Image Analysis ◽  
Mathematical Morphology ◽  
Computation Time ◽  
3D Images ◽  
Structuring Element

Grayscale dilation and erosion are basic transformations of mathematical morphology. Used together or with other transformations, they are very useful tools for image analysis. However, they can be very time consuming, especially with 3D images, and with large structuring elements. Several algorithms have been created to decrease the computation time, some of them with some limitations of shape of structuring element. We have implemented several algorithms, studied their performance in different conditions, and shown that all of them are more efficients than the others in certain conditions. We finally introduce a new structuring element class and a some meta filter designed to select the best algorithm depending on the image and the structuring element, and to smoothely integrate the different algorithms available in the toolkit.

scholarly journals A fast and simple method for the visual enhancement of microcalcifications in digital mammograms based on mathematical morphology

2014 ◽  
Vol 29 (2) ◽  
pp. 108-115
Author(s):  
Tomislav Stojic
Keyword(s):  
Image Analysis ◽  
Real Time ◽  
Mathematical Morphology ◽  
Simple Method ◽  
Processing Task ◽  
Structuring Element ◽  
Visual Enhancement ◽  
Visual Aid ◽  
Analysis Society ◽  
Shape And Size

A fast and simple method for the visual enhancement of small bright details in digital mam- mograms based on mathematical morphology is proposed. By a proper choice of the shape and size of the structuring element, an algorithm for a particular processing task - in this case, for the visual enhancement of microcalcifications in digital mammograms - was designed. The efficiency of the proposed algorithm was tested on publicly available mammograms from the mammographic image analysis society database. In all tested cases (23 mammograms), the proposed method successfully segmented and enhanced the existing microcalcifications, in- dependently verified by medical experts. The proposed procedure may be used both as a visual aid in clinical mammogram analysis or as a preprocessing step for further processing, such as segmentation, classification and detection of microcalcifications. Moreover, the algorithm is very fast and robust, thus applicable to real-time mammogram processing.

Image Analysis and Mathematical Morphology.

Biometrics ◽  
1983 ◽  
Vol 39 (2) ◽  
pp. 536 ◽  
Author(s):  
P. J. Diggle ◽  
J. Serra
Keyword(s):  
Image Analysis ◽  
Mathematical Morphology

3d Confocal Microscopy and Image Analysis for Measurement of Genetic Instability

1999 ◽  
Vol 5 (S2) ◽  
pp. 1022-1023
Author(s):  
C. Ortiz de Solorzano ◽  
K. Chin ◽  
D. Knowles ◽  
A. Jones ◽  
E. Garcia ◽  
...  
Keyword(s):  
Image Analysis ◽  
Confocal Microscopy ◽  
Genetic Instability ◽  
Copy Number ◽  
3D Image ◽  
3D Images ◽  
Tissue Sections ◽  
Total Dna ◽  
Natural Tissue

Solid tumors frequently contain cells that are heterogeneous in the copy number of DNA loci. This fact implies the existence of genetic instability, which may be associated with disease aggressiveness. Accurate measurement of this phenomenon requires analysis of intact nuclei within their natural tissue context. We perform these measurements by preparing >30μm thick tissue sections, labeling them with fluorescent labels for total DNA and for specific DNA loci using fluorescence in situ hybridization (FISH) which retain the transparency of the tissue and acquiring 3D images of the tissue using confocal microscopy (figure 1). In this study, we combined automated 3D image analysis (IA) algorithms for segmenting individual nuclei based on the total DNA stain1 and for segmenting the punctuate FISH signals of DNA loci. This enables us to efficiently enumerate the copy number of specific DNA loci in individual cells and as a function of the cell's location in the tissue.

DIGITAL MAMMOGRAM ENHANCEMENT USING KAPUR MEASURE OF ENTROPY AND MATHEMATICAL MORPHOLOGY

2013 ◽  
Vol 25 (03) ◽  
pp. 1350029 ◽  
Author(s):  
Baljit Singh Khehra ◽  
Amar Partap Singh Pharwaha
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Early Detection ◽  
Contrast Enhancement ◽  
Mathematical Morphology ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Signal To Noise ◽  
Mammogram Image ◽  
Background Contrast

Mammography is the most reliable, effective, low cost and highly sensitive method for early detection of breast cancer. Mammogram analysis usually refers to the processing of mammograms with the goal of finding abnormality presented in the mammogram. Mammogram enhancement is one of the most critical tasks in automatic mammogram image analysis. Main purpose of mammogram enhancement is to enhance the contrast of details and subtle features while suppressing the background heavily. In this paper, a hybrid approach is proposed to enhance the contrast of microcalcifications while suppressing the background heavily, using fuzzy logic and mathematical morphology. First, mammogram is fuzzified using Gaussian fuzzy membership function whose bandwidth is computed using Kapur measure of entropy. After this, mathematical morphology is applied on fuzzified mammogram. Mathematical morphology provides tools for the extraction of microcalcifications even if the microcalcifications are located on a nonuniform background. Main advantage of Kapur measure of entropy over Shannon entropy is that Kapur measure of entropy has α and β parameters that can be used as adjustable values. These parameters can play an important role as tuning parameters in the image processing chain for the same class of images. Experiments have been conducted on images of mini-Mammogram Image Analysis Society (MIAS) database (UK). Experiment results of the proposed approach are compared with histogram equalization (HE), contrast limited adaptive histogram equalization (CLAHE) and fuzzy histogram hyperbolization (FHH) which are well-established image enhancement techniques. In order to validate the results, several different kinds of standard test images (fatty, fatty-glandular and dense-glandular) of mini-MIAS database are considered. Objective image quality assessment parameters: Target-to-background contrast enhancement measurement based on standard deviation (TBCSD), target-to-background contrast enhancement measurement based on entropy (TBCE), contrast improvement index (CII), peak signal-to-noise ratio (PSNR) and average signal-to-noise ratio (ASNR) are used to evaluate the performance of proposed approach. The experimental results show that the proposed approach performs well. This study can be a part of developing a computer-aided diagnosis (CAD) system for early detection of breast cancer.

scholarly journals Three-Dimensional Monitoring of Plant Structural Parameters and Chlorophyll Distribution

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 413 ◽  
Author(s):  
Kenta Itakura ◽  
Itchoku Kamakura ◽  
Fumiki Hosoi
Keyword(s):  
Image Analysis ◽  
Water Stress ◽  
Chlorophyll Content ◽  
Structural Parameters ◽  
Azimuthal Angle ◽  
Three Dimensional ◽  
Plant Structure ◽  
3D Images ◽  
Water Stress Condition ◽  
The Status

Image analysis is widely used for accurate and efficient plant monitoring. Plants have complex three-dimensional (3D) structures; hence, 3D image acquisition and analysis is useful for determining the status of plants. Here, 3D images of plants were reconstructed using a photogrammetric approach, called “structure from motion”. Chlorophyll content is an important parameter that determines the status of plants. Chlorophyll content was estimated from 3D images of plants with color information. To observe changes in the chlorophyll content and plant structure, a potted plant was kept for five days under a water stress condition and its 3D images were taken once a day. As a result, the normalized Red value and the chlorophyll content were correlated; a high R2 value (0.81) was obtained. The absolute error of the chlorophyll content estimation in cross-validation studies was 4.0 × 10−2 μg/mm2. At the same time, the structural parameters (i.e., the leaf inclination angle and the azimuthal angle) were calculated by simultaneously monitoring the changes in the plant’s status in terms of its chlorophyll content and structural parameters. By combining these parameters related to plant information in plant image analysis, early detection of plant stressors, such as water stress, becomes possible.

Silhouette Processing Via Mathematical Morphology with Pose-Aware Structuring Elements Based on 3D Model

2012 ◽  
Vol 17 (4) ◽  
pp. 71-78
Author(s):  
Mirosław Jabłoński
Keyword(s):  
Mathematical Morphology ◽  
3D Model ◽  
Structuring Element ◽  
Software Packages ◽  
Camera Image ◽  
Platform Comparison ◽  
Element Computation ◽  
Camera Parameters ◽  
The Individual

Abstract In the paper, the method of poseaware silhouette processing is presented. Morphological closing is proposed to enhance segmented silhouette object. The contribution of the work is adaptation of structuring element used for mathematical morphology erosions and dilations. It is proposed to use camera parameters, 3D model of the scene, model of the silhouette and its position to compute structuring element adequate to the individual projected to the camera image. Structuring element computation and basic morphology operators were implemented in OpenCL environment and tested on parallel GPU platform. Comparison with utility software packages is provided and results are briefly discussed.

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