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Algorithms in radiology and medical imaging.

As a tool in clinical decision making, algorithms deserve careful consideration. The potential use or abuse of algorithms in rationing health care renders such consideration essential. In radiology and medical imaging, algorithms have been applied as teaching tools in the conference room setting. These teaching decision trees, however, may not be applicable in the clinical situation. If an algorithmic approach to clinical radiology is pursued, several issues should be considered. Specifically, the application, design, designer, economics, and universality of the algorithms must be addressed. As an alternative to the wide dissemination of clinical algorithms, the authors propose the development of consensus opinions among specialists and the promulgation of the principle of radiologist-consultant-decision maker. A decision team is preferable to a decision tree.

Algorithms↗

Prospective evaluation of a sequential pacing and high-energy bidirectional shock algorithm for transvenous cardioversion in patients with ventricular tachycardia.

Rapid ventricular pacing alone or in combination with low- or intermediate-energy shocks has limited efficacy in cardioverting rapid ventricular tachycardia (VT) when delivered through two transvenous catheter electrodes. This prospective study determined the efficacy and safety of an algorithm that used a sequence of rapid ventricular pacing (RVP) and intermediate-energy (5 and 15 J) and high-energy (25J) single, bidirectional shocks delivered by two transvenous catheter electrodes in conjunction with a cutaneous electrode in patients with sustained VT. The bidirectional shock was simultaneously delivered over two electrical vectors via a common right ventricular apical cathode and tow anodes consisting of the superior vena caval catheter electrode and cutaneous patch. The electrical therapy delivered was determined by the cycle length of VT. Slow VT (cycle length greater than 300 msec) was sequentially treated by RVP followed by incremental bidirectional shocks of 5, 15, and 25 J. Rapid VT (cycle length less than 300 msec) was treated with no incremental bidirectional shocks of 15 and 25 J. VT was reinduced to determine reproducibility of the algorithm for episodes that were successfully terminated. For patients in whom the primary algorithm failed, a second algorithm was used that excluded 5 and 15 J shocks and went directly to a 25 J shock. VT was reinduced twice and the secondary algorithm was evaluated. Thus, reproducibility of termination of VT with the primary and secondary algorithm was examined. Fifty episodes of slow VT and 40 episodes of rapid VT were induced in 22 patients (mean left ventricular ejection fraction 31 +/- 14%). Six patients had rapid VT, nine patients had slow VT, and seven patients had both.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗

RSPOP: rough set-based pseudo outer-product fuzzy rule identification algorithm.

System modeling with neuro-fuzzy systems involves two contradictory requirements: interpretability verses accuracy. The pseudo outer-product (POP) rule identification algorithm used in the family of pseudo outer-product-based fuzzy neural networks (POPFNN) suffered from an exponential increase in the number of identified fuzzy rules and computational complexity arising from high-dimensional data. This decreases the interpretability of the POPFNN in linguistic fuzzy modeling. This article proposes a novel rough set-based pseudo outer-product (RSPOP) algorithm that integrates the sound concept of knowledge reduction from rough set theory with the POP algorithm. The proposed algorithm not only performs feature selection through the reduction of attributes but also extends the reduction to rules without redundant attributes. As many possible reducts exist in a given rule set, an objective measure is developed for POPFNN to correctly identify the reducts that improve the inferred consequence. Experimental results are presented using published data sets and real-world application involving highway traffic flow prediction to evaluate the effectiveness of using the proposed algorithm to identify fuzzy rules in the POPFNN using compositional rule of inference and singleton fuzzifier (POPFNN-CRI(S)) architecture. Results showed that the proposed rough set-based pseudo outer-product algorithm reduces computational complexity, improves the interpretability of neuro-fuzzy systems by identifying significantly fewer fuzzy rules, and improves the accuracy of the POPFNN.

Algorithms↗

Theoretical analysis of mutation-adaptive evolutionary algorithms.

Adaptive evolutionary algorithms require a more sophisticated modeling than their static-parameter counterparts. Taking into account the current population is not enough when implementing parameter-adaptation rules based on success rates (evolution strategies) or on premature convergence (genetic algorithms). Instead of Markov chains, we use random systems with complete connections - accounting for a complete, rather than recent, history of the algorithm's evolution. Under the new paradigm, we analyze the convergence of several mutation-adaptive algorithms: a binary genetic algorithm, the 1/5 success rule evolution strategy, a continuous, respectively a dynamic (1+1) evolutionary algorithm.

Algorithms↗

Space complexity of estimation of distribution algorithms.

In this paper, we investigate the space complexity of the Estimation of Distribution Algorithms (EDAs), a class of sampling-based variants of the genetic algorithm. By analyzing the nature of EDAs, we identify criteria that characterize the space complexity of two typical implementation schemes of EDAs, the factorized distribution algorithm and Bayesian network-based algorithms. Using random additive functions as the prototype, we prove that the space complexity of the factorized distribution algorithm and Bayesian network-based algorithms is exponential in the problem size even if the optimization problem has a very sparse interaction structure.

Algorithms↗

A statistical study of a class of cellular evolutionary algorithms.

Parallel evolutionary algorithms, over the past few years, have proven empirically worthwhile, but there seems to be a lack of understanding of their workings. In this paper we concentrate on cellular (fine-grained) models, our objectives being: (1) to introduce a suite of statistical measures, both at the genotypic and phenotypic levels, which are useful for analyzing the workings of cellular evolutionary algorithms; and (2) to demonstrate the application and utility of these measures on a specific example-the cellular programming evolutionary algorithm. The latter is used to evolve solutions to three distinct (hard) problems in the cellular-automata domain: density, synchronization, and random number generation. Applying our statistical measures, we are able to identify a number of trends common to all three problems (which may represent intrinsic properties of the algorithm itself), as well as a host of problem-specific features. We find that the evolutionary algorithm tends to undergo a number of phases which we are able to quantitatively delimit. The results obtained lead us to believe that the measures presented herein may prove useful in the general case of analyzing fine-grained evolutionary algorithms.

Algorithms↗

A quality improvement process for implementing the Texas algorithm for schizophrenia in Ohio.

Medication algorithms developed in Texas are being implemented in a number of states in the United States and internationally. This report describes a quality improvement process adapted from the Texas Medication Algorithm Project that was used to implement the Texas algorithm for schizophrenia in Ohio. A total of 38 physicians were surveyed about their perceptions of barriers to implementation of the guidelines. The physicians generally thought that the schizophrenia algorithm was good, current, and applicable. Although they did not perceive barriers to its implementation, they did not seem to alter their practices to a great extent in response to the algorithm. The results of the study may guide other states in their implementation of algorithms.

Algorithms↗

A real-time scan conversion algorithm on commercially available microprocessors.

We have developed a new ultrasound scan conversion algorithm that can be executed very efficiently on modern microprocessors. Our algorithm is designed to handle the address calculations and input and output (I/O) data loading concurrently with the interpolation. The processing unit's computing power can be dedicated to performing pixel interpolations while the other operations are handled by an independent direct memory access (DMA) controller. By making intelligent use of the I/O transfer capabilities of the DMA controller, the algorithm avoids spending the processing unit's valuable computing cycles in address calculations and nonactive pixel blanking. Furthermore, the new approach speeds up the computation by utilizing the ability of superscalar and very long instruction word (VLIW) processors to perform multiple operations in parallel. Our scan conversion algorithm was implemented on a multimedia and imaging system based on the Texas Instruments TMS320C80 Multimedia Video Processor (MVP). Computing cycles are spent only on predeterminable nonzero output pixels. For example, an execution time of 11.4 ms was achieved when there are 101,829 nonzero output pixels. This algorithm demonstrates a substantial improvement over previous scan conversion algorithms, and its optimized implementation enables modern commercially available programmable processors to support scan conversion at video rates.

Algorithms↗

Development of counterpulsation algorithm for a moving-actuator type pulsatile LVAD.

A pulsatile left ventricular assist device (LVAD) was used to support the aortic blood pumping function of an injured left ventricle, and as a result helped its recovery. It is important to observe a left ventricle's pumping status and to adjust the operating status of a LVAD to reduce the left ventricle's pumping load and thus to enhance its recovery. To observe the left ventricle's pumping status, an electrocardiogram (ECG) signal is generally used because it is a result of the natural heart's blood pumping function. In this paper, we describe the development of an ECG based counterpulsation control algorithm that prevents simultaneous aortic blood co-pumping by a left ventricle and a moving-actuator type pulsatile LVAD and as a result, reduces the natural heart's pumping load. In addition, to verify the algorithm's applicability for LVAD control we designed three ECG based automatic pump control algorithms that use a developed counterpulsation control algorithm. These algorithms control the operating status of a LVAD automatically and, at the same time, maintain a counterpulsing status. The results of in vitro experiments show that the counterpulsing effect between a left ventricle and a LVAD was successfully produced and that the newly designed automatic pump control algorithms met their own control purposes with a counterpulsing effect.

Algorithms↗

EM algorithms without missing data.

Most problems in computational statistics involve optimization of an objective function such as a loglikelihood, a sum of squares, or a log posterior function. The EM algorithm is one of the most effective algorithms for maximization because it iteratively transfers maximization from a complex function to a simple, surrogate function. This theoretical perspective clarifies the operation of the EM algorithm and suggests novel generalizations. Besides simplifying maximization, optimization transfer usually leads to highly stable algorithms with well-understood local and global convergence properties. Although convergence can be excruciatingly slow, various devices exist for accelerating it. Beginning with the EM algorithm, we review in this paper several optimization transfer algorithms of substantial utility in medical statistics.

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The EM algorithm in medical imaging.

This article outlines the statistical developments that have taken place in the use of the EM algorithm in emission and transmission tomography during the past decade or so. We discuss the statistical aspects of the modelling of the projection data for both the emission and transmission cases and define the relevant probability models. This leads to the use of the method of maximum likelihood as a means of estimating the relevant unknown parameters within a given region of a patient's body and to the use of the EM algorithm to compute the reconstruction. Various different types of EM algorithm are discussed, including the SAGE algorithms of Fessler and Hero. The limitations of the EM algorithm, per se, are covered and the need for regularization is stressed. A number of different methods for penalizing the likelihood are described and a number of algorithms for the computation of the penalized EM reconstruction are discussed.

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Analysis of concordance of different haplotype block partitioning algorithms.

BACKGROUND: Different classes of haplotype block algorithms exist and the ideal dataset to assess their performance would be to comprehensively re-sequence a large genomic region in a large population. Such data sets are expensive to collect. Alternatively, we performed coalescent simulations to generate haplotypes with a high marker density and compared block partitioning results from diversity based, LD based, and information theoretic algorithms under different values of SNP density and allele frequency. RESULTS: We simulated 1000 haplotypes using the standard coalescent for three world populations--European, African American, and East Asian--and applied three classes of block partitioning algorithms--diversity based, LD based, and information theoretic. We assessed algorithm differences in number, size, and coverage of blocks inferred under different conditions of SNP density, allele frequency, and sample size. Each algorithm inferred blocks differing in number, size, and coverage under different density and allele frequency conditions. Different partitions had few if any matching block boundaries. However they still overlapped and a high percentage of total chromosomal region was common to all methods. This percentage was generally higher with a higher density of SNPs and when rarer markers were included. CONCLUSION: A gold standard definition of a haplotype block is difficult to achieve, but collecting haplotypes covered with a high density of SNPs, partitioning them with a variety of block algorithms, and identifying regions common to all methods may be the best way to identify genomic regions that harbor SNP variants that cause disease.

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Evaluation of clustering algorithms for protein-protein interaction networks.

BACKGROUND: Protein interactions are crucial components of all cellular processes. Recently, high-throughput methods have been developed to obtain a global description of the interactome (the whole network of protein interactions for a given organism). In 2002, the yeast interactome was estimated to contain up to 80,000 potential interactions. This estimate is based on the integration of data sets obtained by various methods (mass spectrometry, two-hybrid methods, genetic studies). High-throughput methods are known, however, to yield a non-negligible rate of false positives, and to miss a fraction of existing interactions. The interactome can be represented as a graph where nodes correspond with proteins and edges with pairwise interactions. In recent years clustering methods have been developed and applied in order to extract relevant modules from such graphs. These algorithms require the specification of parameters that may drastically affect the results. In this paper we present a comparative assessment of four algorithms: Markov Clustering (MCL), Restricted Neighborhood Search Clustering (RNSC), Super Paramagnetic Clustering (SPC), and Molecular Complex Detection (MCODE). RESULTS: A test graph was built on the basis of 220 complexes annotated in the MIPS database. To evaluate the robustness to false positives and false negatives, we derived 41 altered graphs by randomly removing edges from or adding edges to the test graph in various proportions. Each clustering algorithm was applied to these graphs with various parameter settings, and the clusters were compared with the annotated complexes. We analyzed the sensitivity of the algorithms to the parameters and determined their optimal parameter values. We also evaluated their robustness to alterations of the test graph. We then applied the four algorithms to six graphs obtained from high-throughput experiments and compared the resulting clusters with the annotated complexes. CONCLUSION: This analysis shows that MCL is remarkably robust to graph alterations. In the tests of robustness, RNSC is more sensitive to edge deletion but less sensitive to the use of suboptimal parameter values. The other two algorithms are clearly weaker under most conditions. The analysis of high-throughput data supports the superiority of MCL for the extraction of complexes from interaction networks.

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A MEDLINE categorization algorithm.

BACKGROUND: Categorization is designed to enhance resource description by organizing content description so as to enable the reader to grasp quickly and easily what are the main topics discussed in it. The objective of this work is to propose a categorization algorithm to classify a set of scientific articles indexed with the MeSH thesaurus, and in particular those of the MEDLINE bibliographic database. In a large bibliographic database such as MEDLINE, finding materials of particular interest to a specialty group, or relevant to a particular audience, can be difficult. The categorization refines the retrieval of indexed material. In the CISMeF terminology, metaterms can be considered as super-concepts. They were primarily conceived to improve recall in the CISMeF quality-controlled health gateway. METHODS: The MEDLINE categorization algorithm (MCA) is based on semantic links existing between MeSH terms and metaterms on the one hand and between MeSH subheadings and metaterms on the other hand. These links are used to automatically infer a list of metaterms from any MeSH term/subheading indexing. Medical librarians manually select the semantic links. RESULTS: The MEDLINE categorization algorithm lists the medical specialties relevant to a MEDLINE file by decreasing order of their importance. The MEDLINE categorization algorithm is available on a Web site. It can run on any MEDLINE file in a batch mode. As an example, the top 3 medical specialties for the set of 60 articles published in BioMed Central Medical Informatics & Decision Making, which are currently indexed in MEDLINE are: information science, organization and administration and medical informatics. CONCLUSION: We have presented a MEDLINE categorization algorithm in order to classify the medical specialties addressed in any MEDLINE file in the form of a ranked list of relevant specialties. The categorization method introduced in this paper is based on the manual indexing of resources with MeSH (terms/subheadings) pairs by NLM indexers. This algorithm may be used as a new bibliometric tool.

Abstracting and Indexing↗

Mediator-lipidomics: databases and search algorithms for PUFA-derived mediators.

Lipid mediators (LMs) derived from PUFAs play important roles in health and disease. Databases and search algorithms are crucial, but currently unavailable, for accurate and prompt analysis of LMs via liquid chromatography-ultraviolet-tandem mass spectrometry (LC-UV-MS/MS). A novel algorithm and databases, cognoscitive-contrast-angle algorithm and databases (COCAD), were developed for the identification of LMs based on the integration of standard MS/MS spectra with chromatograms and UV spectra. Segment naming and empirical fragmentation rules were introduced to determine MS/MS ion identities, along with ion intensities used by COCAD in matching the unknown to those of authentic standards. The structures of potential LMs without synthetic and/or authentic products as standards were identified by developing theoretical databases and algorithms based on virtual LC-UV-MS/MS spectra and chromatograms. The performance of these databases and algorithms was tested by identifying LMs in murine tissues. These results indicate that COCAD has many advantages for profiling and identification of LMs compared with the conventional dot-product algorithm.

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[High resolution reconstruction of PET images using the iterative OSEM algorithm].

AIM: Improvement of the spatial resolution in positron emission tomography (PET) by incorporation of the image-forming characteristics of the scanner into the process of iterative image reconstruction. METHODS: All measurements were performed at the whole-body PET system ECAT EXACT HR(+) in 3D mode. The acquired 3D sinograms were sorted into 2D sinograms by means of the Fourier rebinning (FORE) algorithm, which allows the usage of 2D algorithms for image reconstruction. The scanner characteristics were described by a spatially variant line-spread function (LSF), which was determined from activated copper-64 line sources. This information was used to model the physical degradation processes in PET measurements during the course of 2D image reconstruction with the iterative OSEM algorithm. To assess the performance of the high-resolution OSEM algorithm, phantom measurements performed at a cylinder phantom, the hotspot Jaszczack phantom, and the 3D Hoffmann brain phantom as well as different patient examinations were analyzed. RESULTS: Scanner characteristics could be described by a Gaussian-shaped LSF with a full-width at half-maximum increasing from 4.8 mm at the center to 5.5 mm at a radial distance of 10.5 cm. Incorporation of the LSF into the iteration formula resulted in a markedly improved resolution of 3.0 and 3.5 mm, respectively. The evaluation of phantom and patient studies showed that the high-resolution OSEM algorithm not only lead to a better contrast resolution in the reconstructed activity distributions but also to an improved accuracy in the quantification of activity concentrations in small structures without leading to an amplification of image noise or even the occurrence of image artifacts. CONCLUSION: The spatial and contrast resolution of PET scans can markedly be improved by the presented image restauration algorithm, which is of special interest for the examination of both patients with brain disorders and small animals.

Algorithms↗

Impact of stress ulcer prophylaxis algorithm study.

BACKGROUND: In the intensive care unit at Royal Victoria Hospital, we noted that drugs prescribed for stress ulcer prophylaxis were not always indicated or optimal. Accordingly, we implemented an algorithm for stress ulcer prophylaxis to guide the medical team in their decisions. The agents selected for the algorithm were intravenous famotidine and omeprazole suspension or tablets, depending on the available administration route. OBJECTIVE: To evaluate the impact of a treatment algorithm on the appropriateness of prescriptions for stress ulcer prophylaxis. METHODS: A quasi-experimental-type evaluative study was conducted based on a pre-/post-intervention design without a concurrent control group. A total of 555 complete admissions met the selection criteria; 303 patients formed the pre-intervention group, and 252 made up the post-intervention group (exposed to the treatment algorithm). RESULTS: After implementation of the algorithm, the proportion of inappropriate prophylaxis was decreased (95.7% vs 88.2%; p = 0.033). The number of days of inappropriate prophylaxis was also reduced significantly (p = 0.013), as was the cost per patient (p = 0.003) for all admissions. However, no difference was observed when the subgroup of patients who received prophylaxis alone was studied (p = 0.098 and p = 0.918). The presence of bleeding was similar in both groups. CONCLUSIONS: Introduction by pharmacists of a treatment algorithm for stress ulcer prophylaxis in intensive care units allows a reduction of inappropriate prescriptions and thus a reduction in the cost of drugs. The use of omeprazole suspension seems to be an alternative to intravenous histamine2-inhibitors; however, a large-scale study is necessary to confirm the efficacy and safety of proton-pump inhibitors administered by an enteral tube.

Adult↗

Comparison of reconstruction algorithms for optical diffraction tomography.

A recently developed inverse scattering algorithm [A. J. Devaney and M. Dennison, Inverse Probl., 19, 855 (2003) and M. Dennison and A. J. Devaney, Inverse Probl., 20, 1307 (2004)] is described and applied in a computer simulation study of optical diffraction tomography (ODT). The new algorithm is superior to standard ODT reconstruction algorithms, such as the filtered backpropagation algorithm, in applications employing a limited number of scattering experiments (the so-called limited-view case) and also in cases where multiple scattering occurs between the object being interrogated and the (known) background in which the object is embedded. The new algorithm is compared and contrasted with the filtered backpropagation algorithm in a computer simulation of ODT of weakly inhomogeneous cylindrical objects being interrogated in a limited number of scattering experiments employing incident plane waves. Our study has potential applications in biomedical imaging and tomographic microscopy.

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