The Medical Image Understanding and Analysis (MIUA) conference series which began in Oxford in 1997 has become the main UK meeting for discussion and dissemination of research progress in image analysis applied to medicine and the biological sciences. In July 2008 we had the pleasure of hosting the 12th MIUA at the University of Dundee. The conference programme included fifty-one full papers fr...

Direct methods have recently emerged as an effective and efficient tool in automated medical image analysis and become a trend to solve diverse challenging tasks in clinical practise. Compared to traditional methods, direct methods are of much more clinical significance by straightly targeting to the final clinical goal rather than relying on any intermediate steps. These intermediate steps, e....

Problem statement: Image segmentation is the process that subdivides an image into its constituent parts and extracts the objects. It is one of the most critical tasks in automatic image analysis because the subdivided results will affect all the subsequent processes of image analysis, such as object representation and description, feature measurement and even the following higher level tasks s...

We studied two image characteristics, the smoothness and the similarity, which give rise to local and global redundancy in image representation. The smoothness means that the gray level values within a given block vary gradually rather than abruptly. The similarity means that any patterns in an image repeat itself anywhere in the rest of the image. In this sense, we proposed a lossless medical ...

Fractal geometry has been applied widely in the analysis of medical images to characterize the irregular complex tissue structures that do not lend themselves to straightforward analysis with traditional Euclidean geometry. In this study, we treat the nonfractal behaviour of medical images over large-scale ranges by considering their box-counting fractal dimension as a scale-dependent parameter...

PDE-constrained optimization problems find many applications in medical image analysis, for example, neuroimaging, cardiovascular imaging, and oncological imaging. We review related literature and give examples on the formulation, discretization, and numerical solution of PDE-constrained optimization problems for medical imaging. We discuss three examples. The first one is image registration. T...

The 16th Conference on Medical Image Understanding and Analysis (MIUA) was hosted in Swansea University in July 2012. MIUA is the principal UK forum for communicating research progress within the community interested in image analysis applied to medicine and related biological science. It is a single-track conference with oral and poster presentations. Authors were asked to submit 6-page techni...

Texture analysis refers to the branch of imaging science that is concerned with the description of characteristic image properties by textural features. However, there is no universally agreed-upon definition of what image texture is and in general different researchers use different definitions depending upon the particular area of application (Tuceryan & Jain, 1998). In this chapter texture i...

This report describes my research activities in the Hasso Plattner Institute and summarizes my PhD plan and several novel, endto-end trainable approches for analyze medical images using deep learning algorithm. In this report, as an example, we explore diffrent novel methods based on deep learning for brain abnormality detection, recognition and segmentation. This report prepared for doctoral c...