@article{MichallekGenskeNiehuesetal.2022, author = {Michallek, Florian and Genske, Ulrich and Niehues, Stefan Markus and Hamm, Bernd and Jahnke, Paul}, title = {Deep learning reconstruction improves radiomics feature stability and discriminative power in abdominal CT imaging}, series = {European Radiology}, volume = {32}, journal = {European Radiology}, number = {7}, publisher = {Springer}, address = {New York}, issn = {1432-1084}, doi = {10.1007/s00330-022-08592-y}, pages = {4587 -- 4595}, year = {2022}, abstract = {Objectives To compare image quality of deep learning reconstruction (AiCE) for radiomics feature extraction with filtered back projection (FBP), hybrid iterative reconstruction (AIDR 3D), and model-based iterative reconstruction (FIRST). Methods Effects of image reconstruction on radiomics features were investigated using a phantom that realistically mimicked a 65-year-old patient's abdomen with hepatic metastases. The phantom was scanned at 18 doses from 0.2 to 4 mGy, with 20 repeated scans per dose. Images were reconstructed with FBP, AIDR 3D, FIRST, and AiCE. Ninety-three radiomics features were extracted from 24 regions of interest, which were evenly distributed across three tissue classes: normal liver, metastatic core, and metastatic rim. Features were analyzed in terms of their consistent characterization of tissues within the same image (intraclass correlation coefficient >= 0.75), discriminative power (Kruskal-Wallis test p value < 0.05), and repeatability (overall concordance correlation coefficient >= 0.75). Results The median fraction of consistent features across all doses was 6\%, 8\%, 6\%, and 22\% with FBP, AIDR 3D, FIRST, and AiCE, respectively. Adequate discriminative power was achieved by 48\%, 82\%, 84\%, and 92\% of features, and 52\%, 20\%, 17\%, and 39\% of features were repeatable, respectively. Only 5\% of features combined consistency, discriminative power, and repeatability with FBP, AIDR 3D, and FIRST versus 13\% with AiCE at doses above 1 mGy and 17\% at doses >= 3 mGy. AiCE was the only reconstruction technique that enabled extraction of higher-order features. Conclusions AiCE more than doubled the yield of radiomics features at doses typically used clinically. Inconsistent tissue characterization within CT images contributes significantly to the poor stability of radiomics features.}, language = {en} } @article{DinesLiuSchulze2009, author = {Dines, Nicoleta and Liu, Xiaochun and Schulze, Bert-Wolfgang}, title = {Edge quantisation of elliptic operators}, series = {Preprint / Universit{\"a}t Potsdam, Institut f{\"u}r Mathematik, Arbeitsgruppe Partiell}, journal = {Preprint / Universit{\"a}t Potsdam, Institut f{\"u}r Mathematik, Arbeitsgruppe Partiell}, issn = {1437-739X}, doi = {10.1007/s00605-008-0058-y}, year = {2009}, abstract = {The ellipticity of operators on a manifold with edge is defined as the bijectivity of the components of a principal symbolic hierarchy sigma = (sigma(psi), sigma(boolean AND)), where the second component takes values in operators on the infinite model cone of the local wedges. In the general understanding of edge problems there are two basic aspects: Quantisation of edge-degenerate operators in weighted Sobolev spaces, and verifying the ellipticity of the principal edge symbol sigma(boolean AND) which includes the (in general not explicity known) number of additional conditions of trace and potential type on the edge. We focus here on these questions and give explicit answers for a wide class of elliptic operators that are connected with the ellipticity of edge boundary value problems and reductions to the boundary. In particular, we study the edge quantisation and ellipticity for Dirichlet-Neumann operators with respect to interfaces of some codimension on a boundary. We show analogues of the Agranovich-Dynin formula for edge boundary value problems.}, language = {en} } @article{BandyopadhyaySarkarMandaletal.2022, author = {Bandyopadhyay, Soumyadip and Sarkar, Dipankar and Mandal, Chittaranjan and Giese, Holger}, title = {Translation validation of coloured Petri net models of programs on integers}, series = {Acta informatica}, volume = {59}, journal = {Acta informatica}, number = {6}, publisher = {Springer}, address = {New York}, issn = {0001-5903}, doi = {10.1007/s00236-022-00419-z}, pages = {725 -- 759}, year = {2022}, abstract = {Programs are often subjected to significant optimizing and parallelizing transformations based on extensive dependence analysis. Formal validation of such transformations needs modelling paradigms which can capture both control and data dependences in the program vividly. Being value-based with an inherent scope of capturing parallelism, the untimed coloured Petri net (CPN) models, reported in the literature, fit the bill well; accordingly, they are likely to be more convenient as the intermediate representations (IRs) of both the source and the transformed codes for translation validation than strictly sequential variable-based IRs like sequential control flow graphs (CFGs). In this work, an efficient path-based equivalence checking method for CPN models of programs on integers is presented. Extensive experimentation has been carried out on several sequential and parallel examples. Complexity and correctness issues have been treated rigorously for the method.}, language = {en} } @article{OmranianMuellerRoeberNikoloski2015, author = {Omranian, Nooshin and M{\"u}ller-R{\"o}ber, Bernd and Nikoloski, Zoran}, title = {Segmentation of biological multivariate time-series data}, series = {Scientific reports}, volume = {5}, journal = {Scientific reports}, publisher = {Nature Publ. Group}, address = {London}, issn = {2045-2322}, doi = {10.1038/srep08937}, pages = {6}, year = {2015}, abstract = {Time-series data from multicomponent systems capture the dynamics of the ongoing processes and reflect the interactions between the components. The progression of processes in such systems usually involves check-points and events at which the relationships between the components are altered in response to stimuli. Detecting these events together with the implicated components can help understand the temporal aspects of complex biological systems. Here we propose a regularized regression-based approach for identifying breakpoints and corresponding segments from multivariate time-series data. In combination with techniques from clustering, the approach also allows estimating the significance of the determined breakpoints as well as the key components implicated in the emergence of the breakpoints. Comparative analysis with the existing alternatives demonstrates the power of the approach to identify biologically meaningful breakpoints in diverse time-resolved transcriptomics data sets from the yeast Saccharomyces cerevisiae and the diatom Thalassiosira pseudonana.}, language = {en} } @article{ChenLangeAndjelkovicetal.2022, author = {Chen, Junchao and Lange, Thomas and Andjelkovic, Marko and Simevski, Aleksandar and Lu, Li and Krstić, Miloš}, title = {Solar particle event and single event upset prediction from SRAM-based monitor and supervised machine learning}, series = {IEEE transactions on emerging topics in computing / IEEE Computer Society, Institute of Electrical and Electronics Engineers}, volume = {10}, journal = {IEEE transactions on emerging topics in computing / IEEE Computer Society, Institute of Electrical and Electronics Engineers}, number = {2}, publisher = {Institute of Electrical and Electronics Engineers}, address = {[New York, NY]}, issn = {2168-6750}, doi = {10.1109/TETC.2022.3147376}, pages = {564 -- 580}, year = {2022}, abstract = {The intensity of cosmic radiation may differ over five orders of magnitude within a few hours or days during the Solar Particle Events (SPEs), thus increasing for several orders of magnitude the probability of Single Event Upsets (SEUs) in space-borne electronic systems. Therefore, it is vital to enable the early detection of the SEU rate changes in order to ensure timely activation of dynamic radiation hardening measures. In this paper, an embedded approach for the prediction of SPEs and SRAM SEU rate is presented. The proposed solution combines the real-time SRAM-based SEU monitor, the offline-trained machine learning model and online learning algorithm for the prediction. With respect to the state-of-the-art, our solution brings the following benefits: (1) Use of existing on-chip data storage SRAM as a particle detector, thus minimizing the hardware and power overhead, (2) Prediction of SRAM SEU rate one hour in advance, with the fine-grained hourly tracking of SEU variations during SPEs as well as under normal conditions, (3) Online optimization of the prediction model for enhancing the prediction accuracy during run-time, (4) Negligible cost of hardware accelerator design for the implementation of selected machine learning model and online learning algorithm. The proposed design is intended for a highly dependable and self-adaptive multiprocessing system employed in space applications, allowing to trigger the radiation mitigation mechanisms before the onset of high radiation levels.}, language = {en} } @article{AndjelkovićChenSimevskietal.2021, author = {Andjelković, Marko and Chen, Junchao and Simevski, Aleksandar and Schrape, Oliver and Krstić, Miloš and Kraemer, Rolf}, title = {Monitoring of particle count rate and LET variations with pulse stretching inverters}, series = {IEEE transactions on nuclear science : a publication of the IEEE Nuclear and Plasma Sciences Society}, volume = {68}, journal = {IEEE transactions on nuclear science : a publication of the IEEE Nuclear and Plasma Sciences Society}, number = {8}, publisher = {Institute of Electrical and Electronics Engineers}, address = {New York, NY}, issn = {0018-9499}, doi = {10.1109/TNS.2021.3076400}, pages = {1772 -- 1781}, year = {2021}, abstract = {This study investigates the use of pulse stretching (skew-sized) inverters for monitoring the variation of count rate and linear energy transfer (LET) of energetic particles. The basic particle detector is a cascade of two pulse stretching inverters, and the required sensing area is obtained by connecting up to 12 two-inverter cells in parallel and employing the required number of parallel arrays. The incident particles are detected as single-event transients (SETs), whereby the SET count rate denotes the particle count rate, while the SET pulsewidth distribution depicts the LET variations. The advantage of the proposed solution is the possibility to sense the LET variations using fully digital processing logic. SPICE simulations conducted on IHP's 130-nm CMOS technology have shown that the SET pulsewidth varies by approximately 550 ps over the LET range from 1 to 100 MeV center dot cm(2) center dot mg(-1). The proposed detector is intended for triggering the fault-tolerant mechanisms within a self-adaptive multiprocessing system employed in space. It can be implemented as a standalone detector or integrated in the same chip with the target system.}, language = {en} } @article{DimitrievSaposhnikovGoesseletal.1997, author = {Dimitriev, Alexej and Saposhnikov, Vl. V. and G{\"o}ssel, Michael and Saposhnikov, V. V.}, title = {On-line testing by self-dual duplication}, year = {1997}, language = {en} } @article{SaposhnikovMorosovSaposhnikovetal.1998, author = {Saposhnikov, V. V. and Morosov, Andrej and Saposhnikov, Vl. V. and G{\"o}ssel, Michael}, title = {A new design method for self-checking unidirectional combinational circuits}, year = {1998}, language = {en} } @article{SeuringGoesselSogomonyan1998, author = {Seuring, Markus and G{\"o}ssel, Michael and Sogomonyan, Egor S.}, title = {A structural approach for space compaction for concurrent checking and BIST}, year = {1998}, language = {en} } @article{SogomonyanGoessel1995, author = {Sogomonyan, Egor S. and G{\"o}ssel, Michael}, title = {A new parity preserving multi-input signature analyser}, year = {1995}, language = {en} }