In this master thesis methods for increasing temporal resolution when reconstructing radially sampled MRI data have been developed and evaluated. This has been done in two steps; first the order in which data is sampled in k-space has been optimized, and second; temporal filters have been developed in order to utilize the high sampling density in central regions of k-space as a result of the polar sampling geometry to increase temporal resolution while maintaining image quality.By properly designing the temporal filters the temporal resolution is increased by a factor 3–20 depending on other variables such as imageresolution and the size of the time varying areas in the image. The results are obtained from simulated raw data and subsequent reconstruction. The next step should be to acquire and reconstruct raw data to confirm the results. / This Master thesis work was performed at Dept. Radiation Physis, Linköping University, but examined at Dept. Radiation Physics, Umeå University

Η πρόοδος της τεχνολογίας CMOS δίνει τη δυνατότητα σχεδιασμού φθηνών, πολυπύρηνων, κοινής μνήμης, ενσωματωμένων επεξεργαστών. Ωστόσο, η υποστήριξη της συνάφειας της κρυφής μνήμης με κάποια μέθοδο που παρουσιάζει καλή κλιμάκωση απαιτεί σημαντική προσπάθεια. Τα πρωτόκολλα υποκλοπής παρέχουν μία λύση εύκολη στο σχεδιασμό, όμως είναι απαιτητικά σε εύρος ζώνης και κατανάλωση. Επιπλέον, η κλιμάκωσή τους είναι περιορισμένη όταν χρησιμοποιούνται σε αρτηρίες. Τα πρωτόκολλα που κάνουν χρήση ευρετηρίου, ειδικά τα κατανεμημένα, επιφέρουν μικρότερη επιβάρυνση στο δίκτυο. Απαιτούν όμως ελεγκτές ευρετηρίων οι οποίοι είναι δύσκολοι στο σχεδιασμό και καταναλώνουν πολύτιμη μνήμη, επιφάνεια και κατανάλωση εντός του ολοκληρωμένου, κάνοντάς τη λύση αυτή ακατάλληλη για ενσωματωμένα πολυπύρηνα συστήματα. Στην εργασία αυτή, παρουσιάζουμε ένα μηχανισμό διατήρησης της συνάφειας ο οποίος παρουσιάζει καλή κλιμάκωση, και βασίζεται σε απλά πρωτόκολλα υποκλοπής, πάνω όμως σε ένα ιεραρχικό δίκτυο σημείο προς σημείο. Για να μειωθούν δραματικά τα μηνύματα που στέλνονται με ευρεία εκπομπή, προτείνουμε τα Χρονολογικά Φίλτρα, μια λύση βασισμένη στα φίλτρα Bloom. Σε αντίθεση με προηγούμενες προσεγγίσεις, τα Χρονολογικά Φίλτρα (Temporal Filters - TF) είναι εφοδιασμένα με ένα μοναδικό χαρακτηριστικό: την ικανότητα να σβήνουν τα περιεχόμενά τους σε συγχρονισμό - αλλά χωρίς να επικοινωνούν - με τις κρυφές μνήμες. Τα Χρονολογικά Φίλτρα και οι κρυφές μνήμες σβήνουν τα περιεχόμενά τους βασισμένα στις ενέργειες που γίνονται για τη διατήρηση της συνάφειας, παρέχοντας ασφαλές φιλτράρισμα ορισμένων μηνυμάτων του πρωτοκόλλου συνάφειας. Με τον τρόπο αυτό, ξεπερνάμε το πρόβλημα της αφαίρεσης στοιχείων των φίλτρων Bloom, χωρίς τη χρήση επιπλέον μετρητών, μηνυμάτων ή σημάτων, όπως έχουν προταθεί σε προηγούμενες εργασίες. Όλα τα παραπάνω γίνονται χωρίς καμία τροποποίηση των πρωτοκόλλων συνάφειας της κρυφής μνήμης. Ως αποτέλεσμα, η λύση που προτείνεται στην εργασία αυτή, χρησιμοποιεί μικρές δομές που μπορούν να ενσωματωθούν εύκολα στους μεταγωγείς του μέσου διασύνδεσης. Για την αποτίμηση των μηχανισμών που προτείνουμε, χρησιμοποιήθηκε το περιβάλλον προσομοίωσης GEMS - για να μοντελοποιηθούν πολυπύρηνοι επεξεργαστές εντός ολοκληρωμένου με 8 και 16 πυρήνες, με ιδιωτικές κρυφές μνήμες πρώτου και δευτέρου επιπέδου - και η σουίτα μετροπρογραμμάτων SPLASH-2. Τα Χρονολογικά Φίλτρα αποδείχτηκαν ικανά να μειώσουν έως και κατά 74.7\% (κατά μέσο όρο) τα μηνύματα στο μέσο διασύνδεσης. Επιπλέον, τα Χρονολογικά Φίλτρα προσφέρουν τη δυνατότητα μείωσης της στατικής κατανάλωσης, καθώς χρησιμοποιείται η τεχνική Decay στις κρυφές μνήμες. / Advances in CMOS technology are enabling the design of inexpensive, multicore, shared-memory, embedded processors. However, supporting cache coherence in a scalable fashion in these architectures requires considerable effort. Snoop protocols provide an easy-to-design solution but they are greedy bandwidth and power consumers. In addition, their scalability is limited over a broadcast bus. Scalable directory protocols, especially distributed ones, remedy the bandwidth overhead but require hard-to-design directory controllers that consume precious on-chip storage, area, and power, rendering the solution unattractive for embedded multicores. In this work we advocate a scalable coherence solution based on simple broadcast snooping protocols but over a scalable hierarchical point-to-point network. To dramatically cut down on broadcasts we propose Temporal Filtering, a solution based on Bloom filters - a storage-efficient memory structure. In contrast to previous approaches, Temporal Filters (TFs) are equipped with a unique characteristic: the ability to self-clean their contents in concert - but without communicating - with caches. Both TFs and caches decay their contents based on coherence activity, guaranteeing the correctness of coherence filtering. In this way, we overcome the problem of entry removal in the Bloom filters without the need of extra counters, messages, or even extra signals as in previous work and, more importantly, without requiring changes in the underlying cache snoop protocols. As a result, our solution utilizes frugal single-bit structures that can be easily integrated into network switches. For our evaluation we use GEMS to model a 8- and 16-core CMP with private L1/L2 caches of various sizes, and the SPLASH-2 suite. TFs are proven able to reduce the 74.7\% (arithmetic average) of the network messages. In addition, TFs offer also leakage saving opportunities since cache decay is also applied in private caches.

In this master thesis methods for increasing temporal resolution when reconstructing radially sampled MRI data have been developed and evaluated. This has been done in two steps; first the order in which data is sampled in k-space has been optimized, and second; temporal filters have been developed in order to utilize the high sampling density in central regions of k-space as a result of the polar sampling geometry to increase temporal resolution while maintaining image quality.By properly designing the temporal filters the temporal resolution is increased by a factor 3–20 depending on other variables such as imageresolution and the size of the time varying areas in the image. The results are obtained from simulated raw data and subsequent reconstruction. The next step should be to acquire and reconstruct raw data to confirm the results. / This Master thesis work were performed at Dept. Radiation Physis, Linköping University, but examined at Dept. Radiation Physics, Umeå University

<p>In video transmission at low bit rates the challenge is to compress the video with a minimal reduction of the percieved quality. The compression can be adapted to knowledge of which regions in the video sequence are of most interest to the viewer. Region of interest (ROI) video coding uses this information to control the allocation of bits to the background and the ROI. The aim is to increase the quality in the ROI at the expense of the quality in the background. In order for this to occur the typical content of an ROI for a particular application is firstly determined and the actual detection is performed based on this information. The allocation of bits can then be controlled based on the result of the detection.</p><p>In this licenciate thesis existing methods to control bit allocation in ROI video coding are investigated. In particular pre-processing methods that are applied independently of the codec or standard. This makes it possible to apply the method directly to the video sequence without modifications to the codec. Three filters are proposed in this thesis based on previous approaches. The spatial filter that only modifies the background within a single frame and the temporal filter that uses information from the previous frame. These two filters are also combined into a spatio-temporal filter. The abilities of these filters to reduce the number of bits necessary to encode the background and to successfully re-allocate these to the ROI are investigated. In addition the computational compexities of the algorithms are analysed.</p><p>The theoretical analysis is verified by quantitative tests. These include measuring the quality using both the PSNR of the ROI and the border of the background, as well as subjective tests with human test subjects and an analysis of motion vector statistics.</p><p>The qualitative analysis shows that the spatio-temporal filter has a better coding efficiency than the other filters and it successfully re-allocates the bits from the foreground to the background. The spatio-temporal filter gives an improvement in average PSNR in the ROI of more than 1.32 dB or a reduction in bitrate of 31 % compared to the encoding of the original sequence. This result is similar to or slightly better than the spatial filter. However, the spatio-temporal filter has a better performance, since its computational complexity is lower than that of the spatial filter.</p>

In video transmission at low bit rates the challenge is to compress the video with a minimal reduction of the percieved quality. The compression can be adapted to knowledge of which regions in the video sequence are of most interest to the viewer. Region of interest (ROI) video coding uses this information to control the allocation of bits to the background and the ROI. The aim is to increase the quality in the ROI at the expense of the quality in the background. In order for this to occur the typical content of an ROI for a particular application is firstly determined and the actual detection is performed based on this information. The allocation of bits can then be controlled based on the result of the detection. In this licenciate thesis existing methods to control bit allocation in ROI video coding are investigated. In particular pre-processing methods that are applied independently of the codec or standard. This makes it possible to apply the method directly to the video sequence without modifications to the codec. Three filters are proposed in this thesis based on previous approaches. The spatial filter that only modifies the background within a single frame and the temporal filter that uses information from the previous frame. These two filters are also combined into a spatio-temporal filter. The abilities of these filters to reduce the number of bits necessary to encode the background and to successfully re-allocate these to the ROI are investigated. In addition the computational compexities of the algorithms are analysed. The theoretical analysis is verified by quantitative tests. These include measuring the quality using both the PSNR of the ROI and the border of the background, as well as subjective tests with human test subjects and an analysis of motion vector statistics. The qualitative analysis shows that the spatio-temporal filter has a better coding efficiency than the other filters and it successfully re-allocates the bits from the foreground to the background. The spatio-temporal filter gives an improvement in average PSNR in the ROI of more than 1.32 dB or a reduction in bitrate of 31 % compared to the encoding of the original sequence. This result is similar to or slightly better than the spatial filter. However, the spatio-temporal filter has a better performance, since its computational complexity is lower than that of the spatial filter.