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Further, we shall try to demonstrate that structural pattern analysis can be regarded as an effective method for medical image understanding, replacing simple recognition (Figure 141) Structural image analysis can be considered to be a totally new approach to the analysis and description of shapes of selected organs in medical imaging in general [6] Examples of the application of syntactic methods of pattern recognition for the understanding and analysis of the selected medical images presented in this chapter show its usefulness for early diagnosis of some diseases of selected organs The results of analysis of investigations, based on the structural analysis of selected types of medical image, confirm very good properties of our proposed methodology and algorithms The chapter will discuss, in particular, disease symptom recognition tasks for four selected areas of the body and types of medical image: analysis of coronary arteries seen on coronographic images [7,8].



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(aj E[gj ] aj+1 E[gj+1 ]) + a1 E[f1 ]

I have already discussed control flow obfuscation in 10; it is the concept of modifying a program s control flow structure in order to make it less readable. In .NET executables control flow obfuscation is aimed primarily at breaking decompilers and preventing them from producing usable output for the obfuscated program. This can be quite easy because decompilers expect programs to contain sensible control flow graphs that can be easily translated back into high-level language control flow constructs such as loops and conditional statements.





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where i 1 ai = 1. i We note that all the parameters of the recurrency solution above are expressed as a function of E[f1 ] and i. So as to compute them, we rstly compute the value of E[f1 ]. Then we can compute all the other parameters by replacing the already computed E[f1 ]. Now, the calculation of the probabilities pi is quite easy.

One feature that many popular obfuscators support, including Dotfuscator, XenoCode, and the Spices.Net obfuscator is to try and completely prevent disassembly of the obfuscated executable. Depending on the specific program that s used for opening such an executable, it might crash or display a special error message, such as the one in Figure 12.3, displayed by ILDasm 1.1.

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This analysis is aimed at discovering the symptoms of ischemic heart disease the renal pelvis with ureters visible on urograms of these structures [9] An analysis of urograms allows diagnosis of some lesions characteristic of hydronephrosis or extrarenal uremia pancreatic ducts visible on images obtained in the course of ERCP (Endoscopic Retrograde Cholangio-Pancreatography) examinations [10] In this case, the objective of the analysis is early computer-aided diagnosis of neoplastic lesions and pancreatitis the spine and spinal cord visualized on MR images The objective is to detect and diagnose lesions that might evidence a whole range of various disease units (numerous forms of inflammatory conditions to the most serious cases of tumors) The process of recognition will be based mainly on the use of context-free picture grammars and languages of description of shape features, as well as graph grammars used to recognize disease symptoms which can occur in these organs.

There are two general strategies for preventing disassembly and decompilation in .NET assemblies. When aiming specifically at disrupting ILDasm, there are some undocumented metadata entries that are checked by ILDasm when an assembly is loaded. These entries are modified by obfuscators in a way that makes ILDasm display the copyright message from Figure 12.3. Another approach is to simply corrupt the assembly s metadata in some way that would not prevent the CLR from running it, but would break programs that load the assembly into memory and scan its metadata. Corrupting the metadata can be done by inserting bogus references to nonexistent strings, fields, or methods. Some programs don t properly deal with such broken links and simply crash when loading the assembly. This is not a pretty approach for obfuscation, and I would generally recommend against it, especially considering how easy it is for developers of decompilers or disassemblers to work around these kinds of tricks.

Theorem 15.5.3. The energy balance property is achieved if any ring sector (say Ti ) propagates each message it handles with probability pi to the next ring sector, Ti 1 , and with probability 1 pi it propagates the message directly to the sink. The value of each pi is given by the following relation: pi = E[fi 1 ] E[gi ] + E[fi ]

This type of recognition may not only support the diagnosis of disease lesions, but it also constitutes intelligent information systems imitating the method of image interpretation and understanding used by qualified professionals The algorithms proposed in this chapter constitute a new proposal for an efficient and effective analysis of selected organ morphology, aimed at diagnosing pathological lesions in them They also expand current analysis techniques to a considerable degree by offering possibilities to specify the semantic content of images, which can support diagnosis and further treatment directions Moreover, they may also serve to provide a quick indexation and categorization of disease units in medical databases [11] For a proper analysis of the mentioned changes, and for a verification of how advanced their level, an attributed context-free grammar of type LR and a graph grammar of type EDT [12,13] have been.

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