As speckle on ultrasonic B-scan may reveal information relative to tissue structure, the present work attempts to discriminate the various prostatic tissues (normal tissue, benign prostatic hypertrophy and cancer) by means of texture analysis. We select regions of interest by their homogeneous appearance. A pre-processing stage is required to obtain stationary samples. The method used measures the second-order statistics, namely co-occurrence matrices. Fairly good tissue signatures have been obtained with parameters derived from these matrices. Of 37 images processed, 78 percent of the samples were classified with success, which is a high score considering that the images cannot be discriminated visually. However, while such results are obtained when wide regions of interest are investigated (64 × 64 pixels), they are not as good with smaller sample sizes, i.e., when the pathological area is very small.
ReidJ.M.The Measurement of Scattering, in Tissue characterization with Ultrasound., GreenleafJ.F. ed., pp. 81–115 (CRC Press, Boca Raton, 1986).
2.
FlaxS.W.PelcN.J.GloverG.M.GutmannF.D.McLachlanM.Spectral characterization and attenuation measurements in ultrasound, Ultrasonic Imaging5, 95–116 (1983).
3.
RomijnR.L.ThijssenJ.M.OosterveldB.J.VerbeekA.M.Ultrasonic differenciation of intraocular melanomas: parameters and estimation methods, Ultrasonic Imaging13, 27–55 (1991).
4.
FerrariL.A.SankarP.V.FinkM.ShinS.B.ChandlerP.Utilisation de la phase du signal en échographie médicale, Acta Electronica26, 111–120 (1984).
5.
FellinghamL.L.SommerF.G.Ultrasonic characterization of tissue structure in the in-vivo human liver and spleen, IEEE Trans. Sonics Ultrason. SU31, 418–428 (1984).
WagnerR.F.SmithS.W.SandrixJ.M.LopezM.Statistics of speckle in ultrasound B-scans, IEEE Trans. Sonics Ultrasons. SU30, 156–163 (1983).
8.
SmithS.W.TraheyG.E.HubbardS.M.WagnerR.F.Properties of acoustical speckle in the presence of phase aberration. Part II: Correlation lengths, Ultrasonic Imaging10, 29–51 (1988).
9.
OosterveldB.J.ThijssenJ.M.VerhoefW.A.Texture of B-mode echograms 3-D simulations and experiments of the effects of diffraction and scatterer density, Ultrasonic Imaging7, 142–160 (1985).
10.
WengL.ReidJ.M.ShankarP.M.SoetantoK.Ultrasound speckle analysis based on the K distribution, J. Acoust. Soc. Am89, 2292- 2295 (1991).
11.
OosterveldB.J.ThijssenJ.M.HartmanP.RosenbuschG.Preprocessing and Texture Analysis of In-vivo B-mode Echograms, Proc. Sixth European Communities Work-shop, pp. 43–50 (Paris, 1986).
12.
InsanaM.F.WagnerR.F.GarraB.S.MomenanR.ShawkerT.H.Pattern recognition methods for optimizing multivariate tissue signatures in diagnostic ultrasound, Ultrasonic Imaging8, 165–180 (1986).
13.
LayerG.ZunaI.LorentzA.ZerbanH.HaberkornU.BannaschP.Van KaickG.RathU.Computerized ultrasound B-scan texture analysis of experimental fatty liver disease: influence of total lipid content and fat deposit distribution, Ultrasonic Imaging12, 171–188 (1990).
WagnerR.F.InsanaM.F.BrownD.G.Unified approach to the detection and classification of speckle texture in diagnostic ultrasound, Optical Engineering25, 738–742 (1986).
16.
InsanaM.F.WagnerR.F.GarraB.S.BrownD.G.ShawkerT.H.Analysis of ultrasound image texture via generalized Rician statistics, Optical Engineering25, 743–748, (1986).
17.
HaberkornU.ZunaI.LorentzA.ZerbanH.LayerG.Van KaickG.RathU.Echographic tissue characterisation in diffuse parenchymal liver disease: correlation of image structure with histology, Ultrasonic Imaging12, 155–170 (1990).
18.
NicholasD.NassiriD.K.GarbuttP.HillC.R.Tissues characterization from ultrasound B-scan data, Ultrasound Medicine and Biol.12, 135–143 (1986).
19.
McPhersonD.D.AylwardP.E.KnospB.M.BeanJ.A.KerberR.E.CollinsS.M.SkortonD.J.Ultrasound characterization of acute myocardial ischemia by quantitative texture analysis, Ultrasonic Imaging8, 227–240 (1986).
20.
HaralickR.M.ShanmuganK.DinsteinI.Textural Features for Image Classification, IEEE Trans. Syst. Man. Cybern SMC3, 610–621 (1973).
21.
BassetO.Traitement d'images Echographiques de la Prostate. Application à la Chirurgie Assistée par Ordinateur, Thèse de Doctorat, p. 211 (INSA Lyon, 1991).
22.
MetzC.E.ROC methodology in radiologic imaging, Investigative radiology21, 720–733 (1986).
23.
ChodakG.W.WaldW.ParmerE.WatanabeH.OheH.SaitohM.Comparison of digital examination and transrectal ultrasonography for the diagnosis of prostatic cancer, Journal of Urology135, 951–954 (1986).
24.
TerrisM.K.FreihaF.S.McNealJ.E.StameyT.A.Efficacy of tranrectal ultrasound for identification of clinically undetected prostate cancer, Journal of Urology146, 78–84 (1991).
