Author\´s reply [to \´Comments on "Partial-volume Bayesian classification of material mixtures in MR volume data using voxel histograms" by Hamid Soltanian-Zadeh and Joe P. Windham\´]

D.H. Laidlaw replies to comments made on his paper (D.H. Laidlaw et al., ibid., vol. 17, no. 1, p. 74-86, 1998) by H. Soltanian-Zadeh and J.P. Windham (ibid., vol. 17, no. 6, p. 1094, 1998). D.H. Laidlaw says that the concept of optimality always rests on a framework of assumptions. Eigenimage filtering is optimal under a certain set of assumptions. However, D.H. Laidlaw et al.´s voxel histogram method uses different assumptions and, as D.H. Laidlaw demonstrates, produces better results with fewer images. In this communication D.H. Laidlaw first discusses some of the assumptions leading to the eigenimage filtering method, then describe how his assumptions differ and how they lead to a different type of classification method. He then presents results comparing the two methods, addresses the four points raised in the communication by H. Soltanian-Zadeh and J.P. Windham (ibid., vol. 17, no. 6, p. 1094, 1998) and states his conclusions.