Color ad spectral image assessment using novel quality and fidelity techniques

The ongoing development of the digital media has brought a new set of challenges with it. As images containing more than three wavelength bands, often called spectral images, are becoming a more integral part of everyday life, problems in the quality of the RGB reproduction from the spectral images have turned into an important area of research. The notion of image quality is often thought to comprise two distinctive areas – image quality itself and image fidelity, both dealing with similar questions, image quality being the degree of excellence of the image, and image fidelity the measure of the match of the image under study to the original. In this thesis, both image fidelity and image quality are considered, with an emphasis on the influence of color and spectral image features on both. There are very few works dedicated to the quality and fidelity of spectral images. Several novel image fidelity measures were developed in this study, which include kernel similarity measures and 3D-SSIM (structural similarity index). The kernel measures incorporate the polynomial, Gaussian radial basis function (RBF) and sigmoid kernels. The 3D-SSIM is an extension of a traditional gray-scale SSIM measure developed to incorporate spectral data. The novel image quality model presented in this study is based on the assumption that the statistical parameters of the spectra of an image influence the overall appearance. The spectral image quality model comprises three parameters of quality: colorfulness, vividness and naturalness. The quality prediction is done by modeling the preference function expressed in JNDs (just noticeable difference). Both image fidelity measures and the image quality model have proven to be effective in the respective experiments.

CT and PET/CT Hybrid Imaging of Coronary Artery Disease

Coronary artery disease (CAD) is a chronic process that evolves over decades and may culminate in myocardial infarction (MI). While invasive coronary angiography (ICA) is still considered the gold standard of imaging CAD, non-invasive assessment of both the vascular anatomy and myocardial perfusion has become an intriguing alternative. In particular, computed tomography (CT) and positron emission tomography (PET) form an attractive combination for such studies. Increased radiation dose is, however, a concern. Our aim in the current thesis was to test novel CT and PET techniques alone and in hybrid setting in the detection and assessment of CAD in clinical patients. Along with diagnostic accuracy, methods for the reduction of the radiation dose was an important target. The study investigating the coronary arteries of patients with atrial fibrillation (AF) showed that CAD may be an important etiology of AF because a high prevalence of CAD was demonstrated within AF patients. In patients with suspected CAD, we demonstrated that a sequential, prospectively ECG-triggered CT technique was applicable to nearly 9/10 clinical patients and the radiation dose was over 60% lower than with spiral CT. To detect the functional significance of obstructive CAD, a novel software for perfusion quantification, CarimasTM, showed high reproducibility with 15O-labelled water in PET, supporting feasibility and good clinical accuracy. In a larger cohort of 107 patients with moderate 30-70% pre-test probability of CAD, hybrid PET/CT was shown to be a powerful diagnostic method in the assessment of CAD with diagnostic accuracy comparable to that of invasive angiography and fractional flow reserve (FFR) measurements. A hybrid study may be performed with a reasonable radiation dose in a vast majority of the cases, improving the performance of stand-alone PET and CT angiography, particularly when the absolute quantification of the perfusion is employed. These results can be applied into clinical practice and will be useful for daily clinical diagnosis of CAD.

An Image Enhancement Technique using MTF of Human eye

Image filtering is a highly demanded approach of image enhancement in digital imaging systems design. It is widely used in television and camera design technologies to improve the quality of an output image to avoid various problems such as image blurring problem thatgains importance in design of displays of large sizes and design of digital cameras. This thesis proposes a new image filtering method basedon visual characteristics of human eye such as MTF. In contrast to the traditional filtering methods based on human visual characteristics this thesis takes into account the anisotropy of the human eye vision. The proposed method is based on laboratory measurements of the human eye MTF and takes into account degradation of the image by the latter. This method improves an image in the way it will be degraded by human eye MTF to give perception of the original image quality. This thesis gives a basic understanding of an image filtering approach and the concept of MTF and describes an algorithm to perform an image enhancement based on MTF of human eye. Performed experiments have shown quite good results according to human evaluation. Suggestions to improve the algorithm are also given for the future improvements.

Retinal Image Analysis Using Machine Vision

The topic of this thesis is studying how lesions in retina caused by diabetic retinopathy can be detected from color fundus images by using machine vision methods. Methods for equalizing uneven illumination in fundus images, detecting regions of poor image quality due toinadequate illumination, and recognizing abnormal lesions were developed duringthe work. The developed methods exploit mainly the color information and simpleshape features to detect lesions. In addition, a graphical tool for collecting lesion data was developed. The tool was used by an ophthalmologist who marked lesions in the images to help method development and evaluation. The tool is a general purpose one, and thus it is possible to reuse the tool in similar projects.The developed methods were tested with a separate test set of 128 color fundus images. From test results it was calculated how accurately methods classify abnormal funduses as abnormal (sensitivity) and healthy funduses as normal (specificity). The sensitivity values were 92% for hemorrhages, 73% for red small dots (microaneurysms and small hemorrhages), and 77% for exudates (hard and soft exudates). The specificity values were 75% for hemorrhages, 70% for red small dots, and 50% for exudates. Thus, the developed methods detected hemorrhages accurately and microaneurysms and exudates moderately.

Multispectral image compression using the wavelet transform

Multispectral images contain information from several spectral wavelengths and currently multispectral images are widely used in remote sensing and they are becoming more common in the field of computer vision and in industrial applications. Typically, one multispectral image in remote sensing may occupy hundreds of megabytes of disk space and several this kind of images may be received from a single measurement. This study considers the compression of multispectral images. The lossy compression is based on the wavelet transform and we compare the suitability of different waveletfilters for the compression. A method for selecting a wavelet filter for the compression and reconstruction of multispectral images is developed. The performance of the multidimensional wavelet transform based compression is compared to other compression methods like PCA, ICA, SPIHT, and DCT/JPEG. The quality of the compression and reconstruction is measured by quantitative measures like signal-to-noise ratio. In addition, we have developed a qualitative measure, which combines the information from the spatial and spectral dimensions of a multispectral image and which also accounts for the visual quality of the bands from the multispectral images.

New Distance Transforms for Gray Level Image Compression

This thesis deals with distance transforms which are a fundamental issue in image processing and computer vision. In this thesis, two new distance transforms for gray level images are presented. As a new application for distance transforms, they are applied to gray level image compression. The new distance transforms are both new extensions of the well known distance transform algorithm developed by Rosenfeld, Pfaltz and Lay. With some modification their algorithm which calculates a distance transform on binary images with a chosen kernel has been made to calculate a chessboard like distance transform with integer numbers (DTOCS) and a real value distance transform (EDTOCS) on gray level images. Both distance transforms, the DTOCS and EDTOCS, require only two passes over the graylevel image and are extremely simple to implement. Only two image buffers are needed: The original gray level image and the binary image which defines the region(s) of calculation. No other image buffers are needed even if more than one iteration round is performed. For large neighborhoods and complicated images the two pass distance algorithm has to be applied to the image more than once, typically 3 10 times. Different types of kernels can be adopted. It is important to notice that no other existing transform calculates the same kind of distance map as the DTOCS. All the other gray weighted distance function, GRAYMAT etc. algorithms find the minimum path joining two points by the smallest sum of gray levels or weighting the distance values directly by the gray levels in some manner. The DTOCS does not weight them that way. The DTOCS gives a weighted version of the chessboard distance map. The weights are not constant, but gray value differences of the original image. The difference between the DTOCS map and other distance transforms for gray level images is shown. The difference between the DTOCS and EDTOCS is that the EDTOCS calculates these gray level differences in a different way. It propagates local Euclidean distances inside a kernel. Analytical derivations of some results concerning the DTOCS and the EDTOCS are presented. Commonly distance transforms are used for feature extraction in pattern recognition and learning. Their use in image compression is very rare. This thesis introduces a new application area for distance transforms. Three new image compression algorithms based on the DTOCS and one based on the EDTOCS are presented. Control points, i.e. points that are considered fundamental for the reconstruction of the image, are selected from the gray level image using the DTOCS and the EDTOCS. The first group of methods select the maximas of the distance image to new control points and the second group of methods compare the DTOCS distance to binary image chessboard distance. The effect of applying threshold masks of different sizes along the threshold boundaries is studied. The time complexity of the compression algorithms is analyzed both analytically and experimentally. It is shown that the time complexity of the algorithms is independent of the number of control points, i.e. the compression ratio. Also a new morphological image decompression scheme is presented, the 8 kernels' method. Several decompressed images are presented. The best results are obtained using the Delaunay triangulation. The obtained image quality equals that of the DCT images with a 4 x 4

Demonstration Platform for Visual Quality Metrics

This thesis presents two graphical user interfaces for the project DigiQ - Fusion of Digital and Visual Print Quality, a project for computationally modeling the subjective human experience of print quality by measuring the image with certain metrics. After presenting the user interfaces, methods for reducing the computation time of several of the metrics and the image registration process required to compute the metrics, and details of their performance are given. The weighted sample method for the image registration process was able to signifigantly decrease the calculation times while resulting in some error. The random sampling method for the metrics greatly reduced calculation time while maintaining excellent accuracy, but worked with only two of the metrics.

Computational visual quality of digitally printed images

The problem of understanding how humans perceive the quality of a reproduced image is of interest to researchers of many fields related to vision science and engineering: optics and material physics, image processing (compression and transfer), printing and media technology, and psychology. A measure for visual quality cannot be defined without ambiguity because it is ultimately the subjective opinion of an “end-user” observing the product. The purpose of this thesis is to devise computational methods to estimate the overall visual quality of prints, i.e. a numerical value that combines all the relevant attributes of the perceived image quality. The problem is limited to consider the perceived quality of printed photographs from the viewpoint of a consumer, and moreover, the study focuses only on digital printing methods, such as inkjet and electrophotography. The main contributions of this thesis are two novel methods to estimate the overall visual quality of prints. In the first method, the quality is computed as a visible difference between the reproduced image and the original digital (reference) image, which is assumed to have an ideal quality. The second method utilises instrumental print quality measures, such as colour densities, measured from printed technical test fields, and connects the instrumental measures to the overall quality via subjective attributes, i.e. attributes that directly contribute to the perceived quality, using a Bayesian network. Both approaches were evaluated and verified with real data, and shown to predict well the subjective evaluation results.

Visual measurement of laser-arc hybrid welding

Tässä työssä raportoidaan hybridihitsauksesta otettujen suurnopeuskuvasarjojen automaattisen analyysijärjestelmän kehittäminen.Järjestelmän tarkoitus oli tuottaa tietoa, joka avustaisi analysoijaa arvioimaan kuvatun hitsausprosessin laatua. Tutkimus keskittyi valokaaren taajuuden säännöllisyyden ja lisäainepisaroiden lentosuuntien mittaamiseen. Valokaaria havaittiin kuvasarjoista sumean c-means-klusterointimenetelmän avullaja perättäisten valokaarien välistä aikaväliä käytettiin valokaaren taajuuden säännöllisyyden mittarina. Pisaroita paikannettiin menetelmällä, jossa yhdistyi pääkomponenttianalyysi ja tukivektoriluokitin. Kalman-suodinta käytettiin tuottamaan arvioita pisaroiden lentosuunnista ja nopeuksista. Lentosuunnanmääritysmenetelmä luokitteli pisarat niiden arvioitujen lentosuuntien perusteella. Järjestelmän kehittämiseen käytettävissä olleet kuvasarjat poikkesivat merkittävästi toisistaan kuvanlaadun ja pisaroiden ulkomuodon osalta, johtuen eroista kuvaus- ja hitsausprosesseissa. Analyysijärjestelmä kehitettiin toimimaan pienellä osajoukolla kuvasarjoja, joissa oli tietynlainen kuvaus- ja hitsausprosessi ja joiden kuvanlaatu ja pisaroiden ulkomuoto olivat samankaltaisia, mutta järjestelmää testattiin myös osajoukon ulkopuolisilla kuvasarjoilla. Testitulokset osoittivat, että lentosuunnanmääritystarkkuus oli kohtuullisen suuri osajoukonsisällä ja pieni muissa kuvasarjoissa. Valokaaren taajuuden säännöllisyyden määritys oli tarkka useammassa kuvasarjassa.

Classification-Based compression of Multispectral Images

The purpose of this thesis is to present a new approach to the lossy compression of multispectral images. Proposed algorithm is based on combination of quantization and clustering. Clustering was investigated for compression of the spatial dimension and the vector quantization was applied for spectral dimension compression. Presenting algo¬rithms proposes to compress multispectral images in two stages. During the first stage we define the classes' etalons, another words to each uniform areas are located inside the image the number of class is given. And if there are the pixels are not yet assigned to some of the clusters then it doing during the second; pass and assign to the closest eta¬lons. Finally a compressed image is represented with a flat index image pointing to a codebook with etalons. The decompression stage is instant too. The proposed method described in this paper has been tested on different satellite multispectral images from different resources. The numerical results and illustrative examples of the method are represented too.

Spectral Color Appearance Modeling

Kuvien laatu on tutkituimpia ja käytetyimpiä aiheita. Tässä työssä tarkastellaan värin laatu ja spektrikuvia. Työssä annetaan yleiskuva olemassa olevista pakattujen ja erillisten kuvien laadunarviointimenetelmistä painottaen näiden menetelmien soveltaminen spektrikuviin. Tässä työssä esitellään spektriväriulkomuotomalli värikuvien laadunarvioinnille. Malli sovelletaan spektrikuvista jäljennettyihin värikuviin. Malli pohjautuu sekä tilastolliseen spektrikuvamalliin, joka muodostaa yhteyden spektrikuvien ja valokuvien parametrien välille, että kuvan yleiseen ulkomuotoon. Värikuvien tilastollisten spektriparametrien ja fyysisten parametrien välinen yhteys on varmennettu tietokone-pohjaisella kuvamallinnuksella. Mallin ominaisuuksien pohjalta on kehitetty koekäyttöön tarkoitettu menetelmä värikuvien laadunarvioinnille. On kehitetty asiantuntija-pohjainen kyselymenetelmä ja sumea päättelyjärjestelmä värikuvien laadunarvioinnille. Tutkimus osoittaa, että spektri-väri –yhteys ja sumea päättelyjärjestelmä soveltuvat tehokkaasti värikuvien laadunarviointiin.

Early Detection of Alzheimer's Disease Beta-amyloid Pathology -Applicability of Positron Emission Tomography with the Amyloid Radioligand 11C-PIB

Early Detection of Alzheimer's Disease Beta-amyloid Pathology -Applicability of Positron Emission Tomography with the Amyloid Radioligand ¹¹C-PIB Accumulation of beta amyloid (Abeta) in the brain is characteristic for Alzheimer’s disease (AD). Carbon-11 labeled 2-(4’-methylaminophenyl)-6-hydroxybenzothiazole (¹¹C-PIB) is a novel positron emission tomography (PET) amyloid imaging agent that appears to be applicable for in vivo Abeta plaque detection and quantitation. The biodistribution and radiation dosimetry of ¹¹C-PIB were investigated in 16 healthy subjects. The reproducibility of a simplified ¹¹C-PIB quantitation method was evaluated with a test-retest study on 6 AD patients and 4 healthy control subjects. Brain ¹¹C-PIB uptake and its possible association with brain atrophy rates were studied over a two-year follow-up in 14 AD patients and 13 healthy controls. Nine monozygotic and 8 dizygotic twin pairs discordant for cognitive impairment and 9 unrelated controls were examined to determine whether brain Abeta accumulation could be detected with ¹¹C-PIB PET in cognitively intact persons who are at increased genetic risk for AD. The highest absorbed radiation dose was received by the gallbladder wall (41.5 mjuGy/MBq). About 20 % of the injected radioactivity was excreted into urine, and the effective whole-body radiation dose was 4.7 mjuSv/MBq. Such a dose allows repeated scans of individual subjects. The reproducibility of the simplified ¹¹C-PIB quantitation was good or excellent both at the regional level (VAR 0.9-5.5 %) and at the voxel level (VAR 4.2-6.4 %). ¹¹C-PIB uptake did not increase during 24 months’ follow-up of subjects with mild or moderate AD, even though brain atrophy and cognitive decline progressed. Baseline neocortical ¹¹C-PIB uptake predicted subsequent volumetric brain changes in healthy control subjects (r = 0.725, p = 0.005). Cognitively intact monozygotic co-twins – but not dizygotic co-twins – of memory-impaired subjects exhibited increased ¹¹C-PIB uptake (117-121 % of control mean) in their temporal and parietal cortices and the posterior cingulate (p<0.05), when compared with unrelated controls. This increased uptake may be representative of an early AD process, and genetic factors seem to play an important role in the development of AD-like Abeta plaque pathology. ¹¹C-PIB PET may be a useful method for patient selection and follow-up for early-phase intervention trials of novel therapeutic agents. AD might be detectable in high-risk individuals in its presymptomatic stage with ¹¹C-PIB PET, which would have important consequences both for future diagnostics and for research on disease-modifying treatments.

In vivo imaging of vascular adhesion protein 1 - preclinical studies with positron emission tomography

The golden standard in nuclear medicine imaging of inflammation is the use of radiolabeled leukocytes. Although their diagnostic accuracy is good, the preparation of the leukocytes is both laborious and potentially hazardous for laboratory personnel. Molecules involved in leukocyte migration could serve as targets for the development of inflammation imaging agents. An excellent target would be a molecule that is absent or expressed at low level in normal tissues, but is induced or up-regulated at the site of inflammation. Vascular adhesion protein-1 (VAP-1) is a very promising target for in vivo imaging, since it is translocated to the endothelial cell surface when inflammation occurs. VAP-1 functions as an endothelial adhesion molecule that participates in leukocyte recruitment to inflamed tissues. Besides being an adhesion molecule, VAP-1 also has enzymatic activity. In this thesis, the targeting of VAP-1 was studied by using Gallium-68 (68Ga) labeled peptides and an Iodine-124 (124I) labeled antibody. The peptides were designed based on molecular modelling and phage display library searches. The new imaging agents were preclinically tested in vitro, as well as in vivo in animal models. The most promising imaging agent appeared to be a peptide belonging to the VAP-1 leukocyte ligand, Siglec-9 peptide. The 68Ga-labeled Siglec-9 peptide was able to detect VAP-1 positive vasculature in rodent models of sterile skin inflammation and melanoma by positron emission tomography. In addition to peptides, the 124I-labeled antibody showed VAP-1 specific binding both in vitro and in vivo. However, the estimated human radiation dose was rather high, and thus further preclinical studies in disease models are needed to clarify the value of this imaging agent. Detection of VAP-1 on endothelium was demonstrated in these studies and this imaging approach could be used in the diagnosis of inflammatory conditions as well as melanoma. These studies provide a proof-of-concept for PET imaging of VAP-1 and further studies are warranted.

The Possibilities and Dosimetric Limitations of MLC-Based Intensity-Modulated Radiotherapy Delivery and Optimization Techniques

The use of intensity-modulated radiotherapy (IMRT) has increased extensively in the modern radiotherapy (RT) treatments over the past two decades. Radiation dose distributions can be delivered with higher conformality with IMRT when compared to the conventional 3D-conformal radiotherapy (3D-CRT). Higher conformality and target coverage increases the probability of tumour control and decreases the normal tissue complications. The primary goal of this work is to improve and evaluate the accuracy, efficiency and delivery techniques of RT treatments by using IMRT. This study evaluated the dosimetric limitations and possibilities of IMRT in small (treatments of head-and-neck, prostate and lung cancer) and large volumes (primitive neuroectodermal tumours). The dose coverage of target volumes and the sparing of critical organs were increased with IMRT when compared to 3D-CRT. The developed split field IMRT technique was found to be safe and accurate method in craniospinal irradiations. By using IMRT in simultaneous integrated boosting of biologically defined target volumes of localized prostate cancer high doses were achievable with only small increase in the treatment complexity. Biological plan optimization increased the probability of uncomplicated control on average by 28% when compared to standard IMRT delivery. Unfortunately IMRT carries also some drawbacks. In IMRT the beam modulation is realized by splitting a large radiation field to small apertures. The smaller the beam apertures are the larger the rebuild-up and rebuild-down effects are at the tissue interfaces. The limitations to use IMRT with small apertures in the treatments of small lung tumours were investigated with dosimetric film measurements. The results confirmed that the peripheral doses of the small lung tumours were decreased as the effective field size was decreased. The studied calculation algorithms were not able to model the dose deficiency of the tumours accurately. The use of small sliding window apertures of 2 mm and 4 mm decreased the tumour peripheral dose by 6% when compared to 3D-CRT treatment plan. A direct aperture based optimization (DABO) technique was examined as a solution to decrease the treatment complexity. The DABO IMRT technique was able to achieve treatment plans equivalent with the conventional IMRT fluence based optimization techniques in the concave head-and-neck target volumes. With DABO the effective field sizes were increased and the number of MUs was reduced with a factor of two. The optimality of a treatment plan and the therapeutic ratio can be further enhanced by using dose painting based on regional radiosensitivities imaged with functional imaging methods.

Neutronisäteilylle altistuminen käytetyn polttoaineen siirrossa Olkiluodon voimalaitoksella

Tässä työssä on tutkittu OL1/OL2-ydinvoimalaitosten käytetyn polttoaineen siirrossa aiheutuvaa altistusta neutronisäteilylle. Käytetty polttoaine siirretään vedellä täytetyssä käytetyn polttoaineen siirtosäiliössä Castor TVO:ssa OL1/OL2-laitoksilta käytetyn polttoaineen varastolle. Siirtotyön aikana useat eri ammattiryhmiin kuuluvat henkilöt työskentelevät siirtosäiliön välittömässä läheisyydessä, altistuen käytetystä polttoaineesta emittoituvalle fotoni- ja neutronisäteilylle. Aikaisemmista neutronisäteilyannosten mittauksista on todettu, ettei jatkuvalle altistuksen seurannalle ole ollut tarvetta. Tämän työn tarkoitus on selvittää teoreettisilla laskelmilla siirtotyöhön osallistuvan henkilön mahdollisuus saada kirjausrajan ylittävä annos neutronisäteilyä. Neutronisäteilyn annosnopeudet siirtosäiliötä ympäröivässä tilassa on laskettu yhdysvaltalaisella Monte Carlo-menetelmään perustuvalla MCNP-ohjelmalla. MCNP:llä mallinnettiin siirtosäiliö, siirtosäiliön sisältämä polttoaine ja ympäröivä tila kolmella jäähtymisajalla ja kolmella keskimääräisellä maksimipoistopalamalla. Polttoainenippujen isotooppikonsentraatiot ja säteilylähteiden voimakkuudet on laskettu Studsvik SNF-ohjelmalla. Simuloinnin perusteella voidaan todeta, ettei neutronisäteilyannosten jatkuvalle seurannalle ole tarvetta käytetyn polttoaineen siirrossa. Vaikka neutronisäteilyn annosnopeudet voivat nousta siirtosäiliön läheisyydessä suhteellisen suuriksi, ovat siirtosäiliön lähellä tehtävät työt niin lyhytaikaisia, että kirjausrajan ylitystä voidaan pitää hyvin epätodennäköisenä. Johtopäätökset varmistetaan työssä suunnitellulla mittausjärjestelyllä.