Irreversibel komprimering av MRI-bilder med artificiella neuronnätverk som del i tillvägagångssättet

Medical Imagery (MI) has made much progress in the lasttwo decades. Making use of new modalities and improvedaccess to technologies, such as magnetic resonance imaging(MRI), has lead to an increasing amount of images andrelated medical data. The increase in data calls for bettercompression methods to support fast communication andstorage of medical images. In MI the most used compression techniques are JPEGand the more modern JPEG-2000 (JP2). Recent attemptsto improve compression has made use of artificial neuralnetworks (ANN) as part of one or more steps in the compressionprocess. This report tries to compress MRI images using a hybridANN approach mostly based on the JP2 approach.The results were validated and compared using both MSEand PSNR as well as compression ratio. A dataset of 500MRI images from one patient was used in training and testingthe implementation. The results of this study were notcomparable to previous work and it fails to even come closeto the JP2 compression rate. This could largely be due toflaws in the implementation or not enough training of theANN, meaning that the proposed method could still be aviable approach for future research

Irreversibel komprimering av MRI-bilder med artificiella neuronnätverk som del i tillvägagångssättet

Medical Imagery (MI) has made much progress in the lasttwo decades. Making use of new modalities and improvedaccess to technologies, such as magnetic resonance imaging(MRI), has lead to an increasing amount of images andrelated medical data. The increase in data calls for bettercompression methods to support fast communication andstorage of medical images. In MI the most used compression techniques are JPEGand the more modern JPEG-2000 (JP2). Recent attemptsto improve compression has made use of artificial neuralnetworks (ANN) as part of one or more steps in the compressionprocess. This report tries to compress MRI images using a hybridANN approach mostly based on the JP2 approach.The results were validated and compared using both MSEand PSNR as well as compression ratio. A dataset of 500MRI images from one patient was used in training and testingthe implementation. The results of this study were notcomparable to previous work and it fails to even come closeto the JP2 compression rate. This could largely be due toflaws in the implementation or not enough training of theANN, meaning that the proposed method could still be aviable approach for future research

Irreversibel komprimering av MRI-bilder med artificiella neuronnätverk som del i tillvägagångssättet

Medical Imagery (MI) has made much progress in the lasttwo decades. Making use of new modalities and improvedaccess to technologies, such as magnetic resonance imaging(MRI), has lead to an increasing amount of images andrelated medical data. The increase in data calls for bettercompression methods to support fast communication andstorage of medical images. In MI the most used compression techniques are JPEGand the more modern JPEG-2000 (JP2). Recent attemptsto improve compression has made use of artificial neuralnetworks (ANN) as part of one or more steps in the compressionprocess. This report tries to compress MRI images using a hybridANN approach mostly based on the JP2 approach.The results were validated and compared using both MSEand PSNR as well as compression ratio. A dataset of 500MRI images from one patient was used in training and testingthe implementation. The results of this study were notcomparable to previous work and it fails to even come closeto the JP2 compression rate. This could largely be due toflaws in the implementation or not enough training of theANN, meaning that the proposed method could still be aviable approach for future research

The edge of two worlds: A new review and synthesis on Eurasian forest-steppes

Peter, Torok/0000-0002-4428-3327; Anenkhonov, Oleg/0000-0001-8633-7154; Batori, Zoltan/0000-0001-9915-5309; Magnes, Martin/0000-0002-5453-5735WOS: 000442660900001AimsEurasian forest-steppes are among the most complex non-tropical terrestrial ecosystems. Despite their considerable scientific, ecological and economic importance, knowledge of forest-steppes is limited, particularly at the continental scale. Here we provide an overview of Eurasian forest-steppes across the entire zone: (a) we propose an up-to-date definition of forest-steppes, (b) give a short physiogeographic outline, (c) delineate and briefly characterize the main forest-steppe regions, (d) explore forest-steppe biodiversity and conservation status, and (e) outline forest-steppe prospects under predicted climate change. LocationEurasia (29 degrees-56 degrees N, 16 degrees-139 degrees E). Results and ConclusionsForest-steppes are natural or near-natural vegetation complexes of arboreal and herbaceous components (typically distributed in a mosaic pattern) in the temperate zone, where the co-existence of forest and grassland is enabled primarily by the semi-humid to semi-arid climate, complemented by complex interactions of biotic and abiotic factors operating at multiple scales. This new definition includes lowland forest-grassland macromosaics (e.g. in Eastern Europe), exposure-related mountain forest-steppes (e.g. in Inner Asia), fine-scale forest-grassland mosaics (e.g. in the Carpathian Basin) and open woodlands (e.g. in the Middle East). Using criteria of flora, physiognomy, relief and climate, nine main forest-steppe regions are identified and characterized. Forest-steppes are not simple two-phase systems, as they show a high level of habitat diversity, with forest and grassland patches of varying types and sizes, connected by a network of differently oriented edges. Species diversity and functional diversity may also be exceptionally high in forest-steppes. Regarding conservation, we conclude that major knowledge gaps exist in determining priorities at the continental, regional, national and local levels, and in identifying clear target states and optimal management strategies. When combined with other threats, climate change may be particularly dangerous to forest-steppe survival, possibly resulting in compositional changes, rearrangement of the landscape mosaic or even the latitudinal or altitudinal shift of forest-steppes.Orszagos Tudomanyos Kutatasi AlapprogramokOrszagos Tudomanyos Kutatasi Alapprogramok (OTKA) [K 119 225, PD 116114]; Hungarian Government [EFOP-3.6.1-16-2016-00014]; National Youth Excellence Scholarship [NTP-NFTO-16-0623]; NKFIH [K 124796, K 119225]; Russian Federal Budget [AAAA-A17-117011810036-3]Orszagos Tudomanyos Kutatasi Alapprogramok, Grant/Award Number: K 119 225 and PD 116114; Hungarian Government, Grant/Award Number: EFOP-3.6.1-16-2016-00014; National Youth Excellence Scholarship, Grant/Award Number: NTP-NFTO-16-0623; NKFIH, Grant/Award Number: K 124796 and K 119225; Russian Federal Budget, Grant/Award Number: AAAA-A17-117011810036-