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Comments on "Geodesic saliency of watershed contours and hierarchical segmentation"

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1998年第7期20卷 762-763页

作者： Lemarechal, C Fjortoft, R Marthon, P Cubero-Castan, E CNRS INP UMRIRITENSEEIHTLIMA F-31071 Toulouse France French Space Agcy CNES DGA T SH QTIS F-31401 Toulouse France

In a recent paper on morphological image segmentation [1], Najman and Schmitt introduce the powerful concept of edge dynamics. In this communication, we show that the method that they propose to compute the edge dynamics gives erroneous results for certain spatial configurations, and we propose a new algorithm which always yields correct edge dynamics.

关键词： hierarchical segmentation watershed algorithm basin dynamics edge dynamics

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Semi-automatic segmentation of gated blood pool emission tomographic images by watersheds: application to the determination of right and left ejection fractions

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EUROPEAN JOURNAL OF NUCLEAR MEDICINE 1998年第9期25卷 1300-1307页

作者： Mariano-Goulart, D Collet, H Kotzki, PO Zanca, M Rossi, M Univ Montpellier Hosp Dept Nucl Med F-34295 Montpellier 05 France

Tomographic multi-gated blood pool scintigraphy (TMUGA) is a widely available method which permits simultaneous assessment of right and left ventricular ejection fractions. However, the widespread clinical use of this technique is impeded by the lack of segmentation methods dedicated to an automatic analysis of ventricular activities. In this study we evaluated how a watershed algorithm succeeds in providing semi-automatic segmentation of ventricular activities in order to measure right and left ejection fractions by TMUGA. The left ejection fractions of 30 patients were evaluated both with TMUGA and with planar multi-gated blood pool scintigraphy (PMUGA). Likewise, the right ejection fractions of 25 patients were evaluated with first-pass scintigraphy (FP) and with TMUGA. The watershed algorithm was applied to the reconstructed slices in order to group together the voxels whose activity came from one specific cardiac cavity. First, the results of the watershed algorithm were compared with manual drawing around left and right ventricles. Left ejection fractions evaluated by TMUGA with the watershed procedure were not significantly different (p=0.30) from manual outlines whereas a small but significant difference was found for right ejection fractions (p=0.004). Then right and left ejection fractions evaluated by TMUGA (with the semi-automatic segmentation procedure) were compared with the results obtained by FP or PMUGA. Left ventricular ejection fractions evaluated by TMUGA showed an excellent correlation with those evaluated by PMUGA (r=0.93;SEE=5.93%;slope=0.99;intercept = 4.17%). The measurements of these ejection fractions were significantly higher with TMUGA than with PMUGA (P<0.01). The interoperator variability for the measurement of left ejection fractions by TMUGA was 4.6%. Right ventricular ejection fractions evaluated by TMUGA showed a good correlation with those evaluated by FP (r = 0.81;SEE = 6.68%;slope = 1.00;intercept = 0.85%) and were not significa

关键词： tomographic equilibrium gated blood pool scintigraphy ejection fraction watershed algorithm mathematical morphology

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An optimal multiedge detector for SAR image segmentation

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1998年第3期36卷 793-802页

作者： Fjortoft, R Lopes, A Marthon, P Cubero-Castan, E UPS Ctr Etud Spatiales Biospere CESBIO CNES CNRSUMR 5639 F-31401 Toulouse France UPS Ecole Natl Super Electrotechn Elect Informatique Inst Rech Informat Toulouse CNRSUMR 5505INPLab Informat & Math Appl LIMA F-31071 Toulouse France French Space Agcy CNES DGA T SHQTIS F-31401 Toulouse France

Edge detection is a fundamental issue in image analysis. Due to the presence of speckle, which can be modeled as a strong, multiplicative noise, edge detection in synthetic aperture radar (SAR) images is extremely difficult, and edge detectors developed for optical images are inefficient. Several robust operators have been developed for the detection of isolated step edges in speckled images. We propose a new step-edge detector for SAR images, which is optimal in the minimum mean square error (MSSE) sense under a stochastic multiedge model. It computes a normalized ratio of exponentially weighted averages (ROEWA) on opposite sides of the central pixel. This is done in the horizontal and vertical direction, and the magnitude of the two components yields an edge strength map. Thresholding of the edge strength map by a modified version of the watershed algorithm and region merging to eliminate false edges complete an efficient segmentation scheme. Experimental results obtained from simulated SAR images as well as ERS-1 data are presented.

关键词： edge detection multiedge model region merging segmentation speckle synthetic aperture radar (SAR) watershed algorithm

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Morphological characterisation of yeast colony growth on solid media using image processing

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BIOTECHNOLOGY TECHNIQUES 1998年第10期12卷 763-767页

作者： Robinson, A Sadr-kazemi, N Dickason, G Harrison, STL Univ Cape Town ZA-7701 Cape Town South Africa

To rapidly determine the effect of environmental factors on yeast growth, a cell counting and colony sizing image analysis method was developed to characterise colony growth on solid media. A digitised microscopic image of the yeast was analysed using the watershed algorithm for cell number determination and a morphological edge detection for colony size determination. The influence of temperature and physiological stress on yeast growth was then investigated over 12.5 h and data extracted by the image analysis method.

关键词： image processing watershed algorithm morphology growth rate

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SAR image segmentation by morphological methods

SAR image segmentation by morphological methods

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Conference on SAR Image Analysis, Modeling, and Techniques

作者： Lemaréchal, C Fjortoft, R Marthon, P Cubero-Castan, E Lopès, A CNRS INPLab Informat & Math Appl UPSENSEEIHT IRITUMR 5505 F-75700 Paris France

ISBN: (纸本)0819429562

The presence of speckle, which may be modeled as a strong multiplicative noise, makes the segmentation of synthetic aperture radar (SAR) images very difficult. The usual gradient operators yield poor results, but robust operators have been developed specifically for this kind of images. From the edge strength map ("gradient image") created by such an operator, closed skeleton boundaries running through local maxima must be extracted. This can be achieved with the watershed algorithm. However, to reduce the number of false edges, the algorithm must be made less sensitive to speckle. In this article, we compare two different approaches - watershed thresholding and basin dynamics - and propose a new algorithm for the computation of edge dynamics. The improvement brought by basin and edge dynamics is illustrated on ERS-1 images of an agricultural zone.

关键词： basin dynamics edge detection edge dynamics SAR segmentation watershed algorithm

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Automatic watershed segmentation of randomly textured color images

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1997年第11期6卷 1530-1544页

作者： Shafarenko, L Petrou, M Kittler, J Dept. of Electron. & Electr. Eng. Surrey Univ. Guildford

A new method is proposed for processing randomly textured color images, The method is based on a bottom-up segmentation algorithm that takes into consideration both color and texture properties of the image, An LUV gradient is introduced, which provides both a color similarity measure and a basis for applying the watershed transform, The patches of watershed mosaic are merged according to their color contrast until a termination criterion is met, This criterion is based on the topology of the typical processed image, The resulting algorithm does not require any additional information, be it various thresholds, marker extraction rules, and suchlike, thus being suitable for automatic processing of color images, The algorithm is demonstrated within the framework of the problem of automatic granite inspection, The segmentation procedure has been found to be very robust, producing good results not only on granite images, but on the wide range of other noisy color images as well, subject to the termination criterion.

关键词： color texture image segmentation watershed algorithm

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watershed-based segmentation of 3D MR data for volume quantization

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MAGNETIC RESONANCE IMAGING 1997年第6期15卷 679-688页

作者： Sijbers, J Scheunders, P Verhoye, M VanderLinden, A vanDyck, D Raman, E Biomedical Physics Department of Physics University of Antwerp Groenenborgerlaan 171 2020 Antwerpen Belgium Vision Lab Department of Physics University of Antwerp Groenenborgerlaan 171 2020 Antwerpen Belgium Bio-Imaging Lab Department of Physics University of Antwerp Groenenborgerlaan 171 2020 Antwerpen Belgium

The aim of this work is the development of a semiautomatic segmentation technique for efficient and accurate volume quantization of Magnetic Resonance (MR) data, The proposed technique uses a 3D variant of Vincent and Soilles immersion-based watershed algorithm that is applied to the gradient magnitude of the MR data and that produces small volume primitives, The known drawback of the watershed algorithm, oversegmentation, is strongly reduced by a priori application of a 3D adaptive anisotropic diffusion filter to the MR data, Furthermore, oversegmentation is a posteriori reduced by properly merging small volume primitives that have similar gray level distributions, The outcome of the preceding image processing steps is presented to the user for manual segmentation. Through selection of volume primitives, the user quickly segments the first slice, which contains the object of interest, Afterwards, the subsequent slices are automatically segmented by extrapolation, Segmentation results are contingently manually corrected, The proposed segmentation technique is tested on phantom objects, where segmentation errors less than 2% are observed, In addition, the technique is demonstrated on 3D MR data of the mouse head from which the cerebellum is extracted, Volumes of the mouse cerebellum and the mouse brains in tote are calculated. (C) 1997 Elsevier Science Inc.

关键词： 3D segmentation watershed algorithm volume quantization MR imaging

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Segmentation of microscopic images by flooding simulation: A catchment basins merging algorithm 8

Segmentation of microscopic images by flooding simulation: A...

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Conference on Nonlinear Image Processing VIII

作者： deAndrade, MC Bertrand, G Araujo, AA Centro de Desenvolvimento da Tecnologia Nuclear (Brazil) Ecole Superieure d'Ingenieurs en (Brazil) Ecole Superieure d'Ingenieurs en Electrotechnique et Electronique (France) Univ. Federal de Minas Gerais (Brazil)

ISBN: (纸本)0819424374

This work addresses a catchment basins merging algorithm developed to automate the segmentation of microscopic images, which is directly derived from the traditional non-hierarchical watershed algorithm, The proposed merging algorithm, based on digital topology concepts, employs regional criteria to merge the non-significant minima. It can be classified as a region growing method by flooding simulation, working at the scale of the main structures. The shape of the structures is absolutely irrelevant to the merging process. As a characteristic of the flooding simulation methods, the gray level image is viewed as a relief where each gray level is assigned a height. in the proposed method the relief is always flooded from all its local minima which are progressively detected and merged as the flooding takes place. The catchment basins merging process is guided by two parameters: a depth criterion and an area criterion. This solution suppresses the characteristic over-segmentation of the traditional watershed algorithm enabling the direct segmentation of the original image without the need of a previous pre-processing step. Due to the automatic detection of all local minima there is no need of the explicit marker extraction step often required by other flooding simulation methods. It is shown that this solution produces excellent segmentation results allowing the characterization of several materials from their microscopic images.

关键词： image segmentation watershed algorithm edge detection water-fall algorithm image analysis geodesic reconstruction mathematical morphology digital topology region growing flooding simulation

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MRI analysis of lumbar intervertebral disc height in young and older populations

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JOURNAL OF MAGNETIC RESONANCE IMAGING 1997年第5期7卷 880-886页

作者： Roberts, N Gratin, C Whitehouse, GH Magnetic Resonance and Image Analysis Research Centre University of Liverpool P.O. Box 147 Liverpool L69 3BX United Kingdom Centre de Morphologie Mathematique Ecole Nationale Superieure des Mines de Paris 77305 Fontainebleau Cedex France

Measurements of length and section area on MR images are made conventionally by the manipulation of a tracker ball to move a cursor to define end points or delineate boundaries, This operator-dependent method lacks the objectivity that computer-based image analysis techniques, such as edge-detection algorithms, can give, me describe an image analysis routine, based on earlier work by Vincent and Soille using algorithms of mathematical morphology, for automatically extracting the boundary of lumbar intervertebral discs on MR images, This is applied to the automatic measurement of the maximum disc space height and section area of non-degenerate intervertebral discs on MR images obtained for healthy male subjects of two distinct age ranges, i.e. twenty 20- to 30-year-olds and twenty 50- to 60-year-olds. Throughout the levels L1 to L4, intervertebral disc height is found to be significantly greater (P = .0003 to .0161) in the older than in the younger age group. The data support a model of the spine in which the disc adopts a more concave form as a result of microfracturing of the end plates during adult life.

关键词： image analysis intervertebral disc lumbar spine MRI mathematical morphology top-hat algorithm watershed algorithm

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Volume quantization of the mouse cerebellum by semi-automatic 3D segmentation of Magnetic Resonance images

Volume quantization of the mouse cerebellum by semi-automati...

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Conference on Image Processing - Medical Imaging 1996

作者： Sijbers, J VanderLinden, A Scheunders, P VanAudekerke, J VanDyck, D Raman, E UNIV ANTWERP DEPT PHYSB-2020 ANTWERPBELGIUM

ISBN: (纸本)0819420859

The aim of this work is the development of a non-invasive technique for efficient and accurate volume quantization of the cerebellum of mice. This enables an in-vivo study on the development of the cerebellum in order to define possible alterations in cerebellum volume of transgenic mice. We concentrate on a semi-automatic segmentation procedure to extract the cerebellum from 3D magnetic resonance data. The proposed technique uses a 3D variant of Vincent and Soille's immersion based watershed algorithm which is applied to the gradient magnitude of the MR data. The algorithm results in a partitioning of the data in volume primitives. The known drawback of the watershed algorithm, over-segmentation, is strongly reduced by a priori application of an adaptive anisotropic diffusion filter on the gradient magnitude data. In addition, over-segmentation is a posteriori contingently reduced by properly merging volume primitives, based on the minimum description length principle. The outcome of the preceding image processing step is presented to the user for manual segmentation. The first slice which contains the object of interest is quickly segmented by the user through selection of basic image regions. In the sequel, the subsequent slices are automatically segmented. The segmentation results are contingently manually corrected. The technique is tested on phantom objects, where segmentation errors less than 2% were observed. Three-dimensional reconstructions of the segmented data are shown for the mouse cerebellum and the mouse brains in toto.

关键词： 3D image segmentation watershed algorithm volume quantization mouse cerebellum MR Imaging

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