Data Mining Practical Machine Learning Tools and Techniques

Measuring the Strangeness of Strange Attractors

Acts in what Hutchinson (1965) has called the 'ecological theatre' are played out on various scales of space and time. To understand the drama, we must view it on the appropriate scale. Plant ecologists long ago recognized the importance of sampling scale in their descriptions of the dispersion or distribution of species (e.g. Greig-Smith, 1952). However, many ecologists have behaved as if patterns and the processes that produce them are insensitive to differences in scale and have designed their studies with little explicit attention to scale. Kareiva & Andersen (1988) surveyed nearly 100 field experiments in community ecology and found that half were conducted on plots no larger than 1 m in diameter, despite considerable differences in the sizes and types of organisms studied. Investigators addressing the same questions have often conducted their studies on quite different scales. Not surprisingly, their findings have not always matched, and arguments have ensued. The disagreements among conservation biologists over the optimal design of nature reserves (see Simberloff, 1988) are at least partly due to a failure to appreciate scaling differences among organisms. Controversies about the role of competition in structuring animal communities (Schoener, 1982; Wiens, 1983, 1989) or about the degree of coevolution in communities (Connell, 1980; Roughgarden, 1983) may reflect the

https://www.jstor.org/stable/info/2389612

Spatial Scaling in Ecology

Thirty-seven programs that summarize data with histograms and other graphics, calculate measures of spatial continuity, provide smooth least-squares-type maps, and perform stochastic spatial simulation.

GSLIB: Geostatistical Software Library and User's Guide

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(06)68880-6.pdf

Mild cognitive impairment

For risk analysis prior to interventional treatment of brain tumors it is important to identify the functional brain areas affected by the tumor and to estimate their connectivity. Fiber Tracking (FT) on Diffusion Tensor (DT) data has the potential to facilitate this task. Our work is organized in two parts. First, we derive a relationship between diffusion anisotropy and orientation uncertainty of the DT by considering image noise. In order to assess a given FT algorithm with respect to the reconstruction of locally disturbed fiber bundles, this relationship is used for the simulation of white mat-ter lesions in DT data. Then, a deflection based FT algorithm is assessed with our software phantom. The FT algorithm is modified and its parameters are adjusted in order to obtain a fiber bundle reconstruction, which is robust to local fiber disturbance. Thus, it is demonstrated how to evaluate and improve FT algorithms with respect to the reconstruction of locally disturbed fiber bundles on the basis of phantom data with known ground truth. This is expected to improve functional and structural risk analysis for the interventional treatment of brain tumors.

White matter lesion phantom for diffusion tensor data and its application to the assessment of fiber tracking

Analysis of tagged MRI is a valuable tool for assessing regional myocardial function. One major obstacle for existing methods based on feature extraction and registration is the desaturation of the tagging grid over time. We propose a method based on quadrature filters that is invariant to changes in intensity, robust with respect to the grid geometry and provides a dense motion field that allows for the analysis of both global and local movements. A multi-scale and multi-resolution scheme is used to cover different scales of motion and to speed up registration. The described method has been integrated into a prototypical application and applied to a phantom data set and 15 volunteer data sets provided by the STACOM'11. The automatic detection of the 4D motion field took about 130 minutes per MRI data set and about 90 minutes per US data set and resulted in plausible motion fields, which will be quantitatively assessed within the motion tracking challenge at MICCAI 2011.

Motion analysis with quadrature filter based registration of tagged MRI sequences

Objective
The purpose was to assess the volumes of the different hepatic territories and especially the drainage of the right paramedian sector in adult living donor liver transplantation (ALDLT).

Preoperative volume calculation of the hepatic venous draining areas with multi-detector row CT in adult living donor liver transplantation: Impact on surgical procedure.

We discuss interaction tasks and interaction techniques for the planning of soft tissue operations as for example oncologic liver and lung surgery. We focus on techniques to explore the relevant structures, to integrate measurements directly in 3d visualizations and to specify resection volumes. The main contribution of this paper is the introduction of new techniques for 3d measurements and for virtual resections. For both interaction tasks, dedicated widgets have been developed for the direct-manipulative use. In contrast to surgical simulators, which are used for the education of future surgeons, we concentrate on surgeons in the clinical routine and attempt to provide them with preoperative decision-support on the basis of patient-individual data.The selection of the interaction tasks to be supported is based on a questionaire in which 13 surgeons described their praxis of surgery planning and their requirements for computer support. All visualization and interaction techniques are integrated in a software, named SURGERYPLANNER, which exploits the results of image analysis achieved in an earlier project. With the SURGERYPLANNER the anatomical and pathological structures of individual patients are used for surgery planning.

3D-interaction techniques for planning of oncologic soft tissue operations

A quantitative analysis of brain tumors is an important factor that can have direct impact on a patient’s prognosis and treatment. In order to achieve clinical relevance, reproducibility and especially accuracy of a proposed method have to be tested. We propose a framework for the generation of realistic digital phantoms of brain tumors of known volumes and their incorporation into an MR dataset of a healthy volunteer. Deformations that occur due to tumor growth inside the brain are simulated by means of a biomechanical model. Furthermore, a model for the amount of edema at each voxel is included as well as a simulation of contrast enhancement, which provides us with an additional characterization of the tumor. A “ground truth” is generally not available for brain tumors. Our proposed framework provides a flexible tool to generate representative datasets with known ground truth, which is essential for the validation and comparison of current and new quantitative approaches. Experiments are carried out using a semi-automated volumetry approach for a set of generated tumor datasets.

/pdf/a-framework-for-the-generation-of-realistic-brain-tumor-q16fjruy13.pdf

Heinz-Otto Peitgen

Papers

White matter lesion phantom for diffusion tensor data and its application to the assessment of fiber tracking

Motion analysis with quadrature filter based registration of tagged MRI sequences

Preoperative volume calculation of the hepatic venous draining areas with multi-detector row CT in adult living donor liver transplantation: Impact on surgical procedure.

3D-interaction techniques for planning of oncologic soft tissue operations

A Framework for the Generation of Realistic Brain Tumor Phantoms and Applications