Suunnittelutason parametrisointi Kactus2:ssa

Embedded systems are growing larger and more complex. Even now, current system designs can contain hundreds of Intellectual Property (IP) components. To keep up with productivity, the reusability of the IP components must be improved. This is the scope of IEEE standard IP-XACT. This thesis is based on Kactus2, an open source IP-XACT tool developed at Tampere University of Technology. Kactus2 provides a graphical user interface for System-on-Chip and embedded system IP packing, design capture and VHDL/Verilog code generation. This thesis describes the development and implementation of version 2.8 of Kactus2. The requirements and solutions are presented in detail for each of the new features and improvements implemented in version 2.8. Alternative solutions are presented, and the selected alternatives are justified. Possible future implementations are also given. In version 2.8, the parameter usage of IP components is improved through the use of universally unique IDs (UUID), which requires many changes e.g. to the IP-XACT Component editors. New features include parameter importing, design level configuration through parameters and a parameter propagation mechanism. Remapping IP-XACT Memory Maps through the use of Remap States and memory Remap Elements has also been added. To facilitate the storing of hierarchical IP components, a new save action has been added to the Kactus2 toolbar. Version 2.8 of Kactus2 was released according to its schedule. The development of the version is considered a success, as it improves the design level parameterization in Kactus2 while incorporating additional new features. Within a month of its release, Kactus2 version 2.8 has been downloaded over 200 times, and its benefits over the previous version are confirmed by industrial System-on-Chip developers

Python API for Kactus2 IP-XACT tool

System-on-chip design is highly reliant on efficient tooling and commonly agreed standards. IP-XACT is the de-facto industry standard for exchanging design data, yet tool flows fail to fully leverage the information within. We present a Python application programming interface for Kactus2, an open-source IP-XACT design tool to improve the utilization of the standard in tool flows. The Python programming language is well understood, fast to develop and easy to interface with which motivated the language choice. We demonstrate the API applicability in a use case as a part of a recently taped-out System-on-Chip ASIC implementation.acceptedVersionPeer reviewe

Computing in Cardiology 2016

Cardiac, respiratory, and patient body motion artifacts degrade the image quality and quantitative accuracy of the nuclear medicine imaging which may lead to incorrect diagnosis, unnecessary treatment and insufficient therapy. We present a new miniaturized system including joint micro electromechanical (MEMS) accelerometer and gyroscope sensors for simultaneous extraction of cardiac and respiratory signals. We employ two tri-axial joint MEMS sensors for selecting an optimal trigger point in a cardiac and respiratory cycle. The 6-axis motion sensing helps to detect candidate features for cardiac and respiratory gating in Positron emission tomography (PET) imaging. The aim of this study was to validate MEMS-derived signals against traditional Real-time Position Management (RPM) and electrocardiography (ECG) measurement systems in 4 healthy volunteers. High agreement and correlation were found between cardiac and respiratory cycle intervals. These promising first results warrant for further investigations. </p

Imaging of αvβ3 integrin expression in experimental myocardial ischemia with [68Ga]NODAGA-RGD positron emission tomography

Abstract Background Radiolabeled RGD peptides detect αvβ3 integrin expression associated with angiogenesis and extracellular matrix remodeling after myocardial infarction. We studied whether cardiac positron emission tomography (PET) with [68Ga]NODAGA-RGD detects increased αvβ3 integrin expression after induction of flow-limiting coronary stenosis in pigs, and whether αvβ3 integrin is expressed in viable ischemic or injured myocardium. Methods We studied 8 Finnish landrace pigs 13 ± 4 days after percutaneous implantation of a bottleneck stent in the proximal left anterior descending coronary artery. Antithrombotic therapy was used to prevent stent occlusion. Myocardial uptake of [68Ga]NODAGA-RGD (290 ± 31 MBq) was evaluated by a 62 min dynamic PET scan. The ischemic area was defined as the regional perfusion abnormality during adenosine-induced stress by [15O]water PET. Guided by triphenyltetrazolium chloride staining, tissue samples from viable and injured myocardial areas were obtained for autoradiography and histology. Results Stent implantation resulted in a partly reversible myocardial perfusion abnormality. Compared with remote myocardium, [68Ga]NODAGA-RGD PET showed increased tracer uptake in the ischemic area (ischemic-to-remote ratio 1.3 ± 0.20, p = 0.0034). Tissue samples from the injured areas, but not from the viable ischemic areas, showed higher [68Ga]NODAGA-RGD uptake than the remote non-ischemic myocardium. Uptake of [68Ga]NODAGA-RGD correlated with immunohistochemical detection of αvβ3 integrin that was expressed in the injured myocardial areas. Conclusions Cardiac [68Ga]NODAGA-RGD PET demonstrates increased myocardial αvβ3 integrin expression after induction of flow-limiting coronary stenosis in pigs. Localization of [68Ga]NODAGA-RGD uptake indicates that it reflects αvβ3 integrin expression associated with repair of recent myocardial injury

Quantification of porcine myocardial perfusion with modified dual bolus MRI : a prospective study with a PET reference

Abstract Background The reliable quantification of myocardial blood flow (MBF) with MRI, necessitates the correction of errors in arterial input function (AIF) caused by the T1 saturation effect. The aim of this study was to compare MBF determined by a traditional dual bolus method against a modified dual bolus approach and to evaluate both methods against PET in a porcine model of myocardial ischemia. Methods Local myocardial ischemia was induced in five pigs, which were subsequently examined with contrast enhanced MRI (gadoteric acid) and PET (O-15 water). In the determination of MBF, the initial high concentration AIF was corrected using the ratio of low and high contrast AIF areas, normalized according to the corresponding heart rates. MBF was determined from the MRI, during stress and at rest, using the dual bolus and the modified dual bolus methods in 24 segments of the myocardium (total of 240 segments, five pigs in stress and rest). Due to image artifacts and technical problems 53% of the segments had to be rejected from further analyses. These two estimates were later compared against respective rest and stress PET-based MBF measurements. Results Values of MBF were determined for 112/240 regions. Correlations for MBF between the modified dual bolus method and PET was rs = 0.84, and between the traditional dual bolus method and PET rs = 0.79. The intraclass correlation was very good (ICC = 0.85) between the modified dual bolus method and PET, but poor between the traditional dual bolus method and PET (ICC = 0.07). Conclusions The modified dual bolus method showed a better agreement with PET than the traditional dual bolus method. The modified dual bolus method was found to be more reliable than the traditional dual bolus method, especially when there was variation in the heart rate. However, the difference between the MBF values estimated with either of the two MRI-based dual-bolus methods and those estimated with the gold-standard PET method were statistically significant

Quantification of porcine myocardial perfusion with modified dual bolus MRI-A prospective study with a PET reference

BackgroundThe reliable quantification of myocardial blood flow (MBF) with MRI, necessitates the correction of errors in arterial input function (AIF) caused by the T1 saturation effect. The aim of this study was to compare MBF determined by a traditional dual bolus method against a modified dual bolus approach and to evaluate both methods against PET in a porcine model of myocardial ischemia.MethodsLocal myocardial ischemia was induced in five pigs, which were subsequently examined with contrast enhanced MRI (gadoteric acid) and PET (O-15 water). In the determination of MBF, the initial high concentration AIF was corrected using the ratio of low and high contrast AIF areas, normalized according to the corresponding heart rates. MBF was determined from the MRI, during stress and at rest, using the dual bolus and the modified dual bolus methods in 24 segments of the myocardium (total of 240 segments, five pigs in stress and rest). Due to image artifacts and technical problems 53% of the segments had to be rejected from further analyses. These two estimates were later compared against respective rest and stress PET-based MBF measurements.ResultsValues of MBF were determined for 112/240 regions. Correlations for MBF between the modified dual bolus method and PET was rs = 0.84, and between the traditional dual bolus method and PET rs = 0.79. The intraclass correlation was very good (ICC = 0.85) between the modified dual bolus method and PET, but poor between the traditional dual bolus method and PET (ICC = 0.07).ConclusionsThe modified dual bolus method showed a better agreement with PET than the traditional dual bolus method. The modified dual bolus method was found to be more reliable than the traditional dual bolus method, especially when there was variation in the heart rate. However, the difference between the MBF values estimated with either of the two MRI-based dual-bolus methods and those estimated with the gold-standard PET method were statistically significant.</div

Quantification of Myocardial Blood Flow by Machine Learning Analysis of Modified Dual Bolus MRI Examination

Contrast-enhanced magnetic resonance imaging (MRI) is a promising method for estimating myocardial blood flow (MBF). However, it is often affected by noise from imaging artefacts, such as dark rim artefact obscuring relevant features. Machine learning enables extracting important features from such noisy data and is increasingly applied in areas where traditional approaches are limited. In this study, we investigate the capacity of machine learning, particularly support vector machines (SVM) and random forests (RF), for estimating MBF from tissue impulse response signal in an animal model. Domestic pigs (n = 5) were subjected to contrast enhanced first pass MRI (MRI-FP) and the impulse response at different regions of the myocardium (n = 24/pig) were evaluated at rest (n = 120) and stress (n = 96). Reference MBF was then measured using positron emission tomography (PET). Since the impulse response may include artefacts, classification models based on SVM and RF were developed to discriminate noisy signal. In addition, regression models based on SVM, RF and linear regression (for comparison) were developed for estimating MBF from the impulse response at rest and stress. The classification and regression models were trained on data from 4 pigs (n = 168) and tested on 1 pig (n = 48). Models based on SVM and RF outperformed linear regression, with higher correlation (R2SVM  = 0.81, R2RF  = 0.74, R2linear_regression  = 0.60; ρSVM = 0.76, ρRF = 0.76, ρlinear_regression = 0.71) and lower error (RMSESVM = 0.67 mL/g/min, RMSERF = 0.77 mL/g/min, RMSElinear_regression = 0.96 mL/g/min) for predicting MBF from MRI impulse response signal. Classifier based on SVM was optimal for detecting impulse response signals with artefacts (accuracy = 92%). Modified dual bolus MRI signal, combined with machine learning, has potential for accurately estimating MBF at rest and stress states, even from signals with dark rim artefacts. This could provide a protocol for reliable and easy estimation of MBF, although further research is needed to clinically validate the approach.</p

Suunnittelutason parametrisointi Kactus2:ssa

Embedded systems are growing larger and more complex. Even now, current system designs can contain hundreds of Intellectual Property (IP) components. To keep up with productivity, the reusability of the IP components must be improved. This is the scope of IEEE standard IP-XACT. This thesis is based on Kactus2, an open source IP-XACT tool developed at Tampere University of Technology. Kactus2 provides a graphical user interface for System-on-Chip and embedded system IP packing, design capture and VHDL/Verilog code generation. This thesis describes the development and implementation of version 2.8 of Kactus2. The requirements and solutions are presented in detail for each of the new features and improvements implemented in version 2.8. Alternative solutions are presented, and the selected alternatives are justified. Possible future implementations are also given. In version 2.8, the parameter usage of IP components is improved through the use of universally unique IDs (UUID), which requires many changes e.g. to the IP-XACT Component editors. New features include parameter importing, design level configuration through parameters and a parameter propagation mechanism. Remapping IP-XACT Memory Maps through the use of Remap States and memory Remap Elements has also been added. To facilitate the storing of hierarchical IP components, a new save action has been added to the Kactus2 toolbar. Version 2.8 of Kactus2 was released according to its schedule. The development of the version is considered a success, as it improves the design level parameterization in Kactus2 while incorporating additional new features. Within a month of its release, Kactus2 version 2.8 has been downloaded over 200 times, and its benefits over the previous version are confirmed by industrial System-on-Chip developers