Consolidation whole abdomen irradiation following adjuvant carboplatin-paclitaxel based chemotherapy for advanced uterine epithelial cancer: feasibility, toxicity and outcomes.

BACKGROUND: To evaluate feasibility and preliminary outcomes associated with sequential whole abdomen irradiation (WAI) as consolidative treatment following comprehensive surgery and systemic chemotherapy for advanced endometrial cancer. METHODS: We conducted a retrospective analysis of patients treated at our institution from 2000 to 2011. Inclusion criteria were stage III-IV endometrial cancer patients with histological proof of one or more sites of extra-uterine abdomen-confined disease, treated with WAI as part of multimodal therapy. Endpoints were feasibility, acute toxicity, late effects, recurrence-free survival (RFS) and overall survival (OS). Twenty patients were identified. Chemotherapy consisted of 3 to 6 cycles of a platinum-paclitaxel regimen in 18 patients. WAI was delivered using conventional technique to a median total dose of 27.5 Gy. RESULTS: No grade 4 toxicities occurred during chemotherapy or radiotherapy. No radiation dose reduction was necessary. Three patients developed small bowel obstruction, all in the context of recurrent intraperitoneal disease. Kaplan-Meier estimates and 95% confidence intervals for RFS and OS at one year were 63% (38-80%) and 83% (56-94%) and at 3 years 57% (33-76%) and 62% (34-81%), respectively. On univariate Cox analysis, stage IVB and serous papillary (SP) histology were found to be statistically significantly (at the p = 0.05 level) associated with worse RFS and OS. The peritoneal cavity was the most frequent site of initial failure. CONCLUSIONS: Consolidative WAI following chemotherapy is feasible and can be performed without interruption with manageable acute and late toxicity. Patients with endometrioid adenocarcinoma, especially stage FIGO III, had favorable outcomes possibly meriting prospective evaluation of the addition of WAI following chemotherapy in selected patients. Patients with SP do poorly and do not routinely benefit from this approach.

Highlight Removal in Spectral Images

Monissasovelluksissa on hyvin tärkeää vähentää valolähteen vaikutusta kohteen oikean värin havainnoimiseksi. Tämä on tarpeen mm. virtuaalisissa museoissa, telelääketieteessä, verkkokaupassa ja verkkorahassa. Tässä tutkielmassa on kehitetty tekniikkaa kirkkaiden heijastusten poistoon spektrikuvista. Työ sisältää katsauksen yleisen värillisen kuvan ymmärtämiseen, mihin perustuen analysoitiin erilaisia kirkkaiden heijastusten poistO'tekniikoita. Työssä kehitettiin uusi kirkkaiden heijastusten poistO'menetelmä, joka perustuu dikromaattiseen heijastus-malliin, joka kuvaa spektrisen datan objektin omaan väriin ja valaisevan valon väriin perustuen. Ehdotettu kirkkaiden heijastusten poistO'menetelmä hyödyntää erilaisia olemassaolevia menetelmiä, kuten pääkomponenttimenetelmää ja tiedon luokittelu-menetelmää. Yritys kehittää nopeasti toimiva algoritmi, joka myös suoriutuu tehtävästä hyvin, on onnistunut. Kokeet toteutettiin ehdotetun menetelmän mukaisesti ja toimivalla algoritmilla saatiin halutut lopputulokset. Edelleentyö sisältää ehdotuksia esitetyn algoritmin parantamiseksi.

Evaluation and comparison of current fetal ultrasound image segmentation methods for biometric measurements: a grand challenge.

This paper presents the evaluation results of the methods submitted to Challenge US: Biometric Measurements from Fetal Ultrasound Images, a segmentation challenge held at the IEEE International Symposium on Biomedical Imaging 2012. The challenge was set to compare and evaluate current fetal ultrasound image segmentation methods. It consisted of automatically segmenting fetal anatomical structures to measure standard obstetric biometric parameters, from 2D fetal ultrasound images taken on fetuses at different gestational ages (21 weeks, 28 weeks, and 33 weeks) and with varying image quality to reflect data encountered in real clinical environments. Four independent sub-challenges were proposed, according to the objects of interest measured in clinical practice: abdomen, head, femur, and whole fetus. Five teams participated in the head sub-challenge and two teams in the femur sub-challenge, including one team who tackled both. Nobody attempted the abdomen and whole fetus sub-challenges. The challenge goals were two-fold and the participants were asked to submit the segmentation results as well as the measurements derived from the segmented objects. Extensive quantitative (region-based, distance-based, and Bland-Altman measurements) and qualitative evaluation was performed to compare the results from a representative selection of current methods submitted to the challenge. Several experts (three for the head sub-challenge and two for the femur sub-challenge), with different degrees of expertise, manually delineated the objects of interest to define the ground truth used within the evaluation framework. For the head sub-challenge, several groups produced results that could be potentially used in clinical settings, with comparable performance to manual delineations. The femur sub-challenge had inferior performance to the head sub-challenge due to the fact that it is a harder segmentation problem and that the techniques presented relied more on the femur's appearance.

Fast gas chromatography and negative-ion chemical ionization tandem mass spectrometry for forensic analysis of cannabinoids in whole blood.

The present work describes a fast gas chromatography/negative-ion chemical ionization tandem mass spectrometric assay (Fast GC/NICI-MS/MS) for analysis of tetrahydrocannabinol (THC), 11-hydroxy-tetrahydrocannabinol (THC-OH) and 11-nor-9-carboxy-tetrahydrocannabinol (THC-COOH) in whole blood. The cannabinoids were extracted from 500 microL of whole blood by a simple liquid-liquid extraction (LLE) and then derivatized by using trifluoroacetic anhydride (TFAA) and hexafluoro-2-propanol (HFIP) as fluorinated agents. Mass spectrometric detection of the analytes was performed in the selected reaction-monitoring mode on a triple quadrupole instrument after negative-ion chemical ionization. The assay was found to be linear in the concentration range of 0.5-20 ng/mL for THC and THC-OH, and of 2.5-100 ng/mL for THC-COOH. Repeatability and intermediate precision were found less than 12% for all concentrations tested. Under standard chromatographic conditions, the run cycle time would have been 15 min. By using fast conditions of separation, the assay analysis time has been reduced to 5 min, without compromising the chromatographic resolution. Finally, a simple approach for estimating the uncertainty measurement is presented.

Työn ja muun elämän yhteensovittaminen ja sen sukupuolittunut ulottuvuus: analyysi mediateksteistä

Tutkimuksen tarkoituksena on selvittää, miten mediatekstit kuvaavat naisten ja miesten työn ja muun elämän yhteensovittamista. Tavoitteena on tutkia sitä, miten media rakentaa ja uusintaa suomalaisessa yhteiskunnassa vallitsevia sukupuolikäsityksiä ja stereotypioita työn ja muun elämän yhdistämistä käsittelevissä lehtiteksteissä. Lisäksi tavoitteena on analysoida sitä, minkälaisia merkityksiä mediatekstit synnyttävät työstä ja yksityiselämästä. Tutkimus on luonteeltaan laadullinen ja tutkimusmetodina on käytetty diskurssianalyysia. Tutkimusaineisto koostuu 17 suomalaisesta lehtitekstistä. Tekstien valinnassa oli tärkeää se, että ne käsittelevät työn ja muun elämän yhteensovittamista mahdollisimman monipuolisesti. Tutkimustulokset osoittavat, että media uusintaa olemassa olevia sukupuolikäsityksiä työn ja muun elämän yhteensovittamisessa.Lisäksi kävi ilmi työn tekemisen arvostaminen. Muu elämä rakennetaan pääsääntöisesti työssäkäynnin ympärille, vaikka mahdollisuuksia omaan aikaan ja yksityiselämään pidetään hyvin tärkeinä. Yhteiskunnan arvot ja kulttuuri ovat mediatekstien luoman kuvan taustalla. Tämä sanelee osaltaan sen, miten sukupuolta työn ja muun elämän yhteensovittamisessa on lehdissä käsitelty.

Selecting Wavelet Filter for Compression of Spectra from Multispectral Images

The problem of selecting anappropriate wavelet filter is always present in signal compression based on thewavelet transform. In this report, we propose a method to select a wavelet filter from a predefined set of filters for the compression of spectra from a multispectral image. The wavelet filter selection is based on the Learning Vector Quantization (LVQ). In the training phase for the test images, the best wavelet filter for each spectrum has been found by a careful compression-decompression evaluation. Certain spectral features are used in characterizing the pixel spectra. The LVQ is used to form the best wavelet filter class for different types of spectra from multispectral images. When a new image is to be compressed, a set of spectra from that image is selected, the spectra are classified by the trained LVQand the filter associated to the largest class is selected for the compression of every spectrum from the multispectral image. The results show, that almost inevery case our method finds the most suitable wavelet filter from the pre-defined set for the compression.

Lossless compression of hyperspectral images

Technological progress has made a huge amount of data available at increasing spatial and spectral resolutions. Therefore, the compression of hyperspectral data is an area of active research. In somefields, the original quality of a hyperspectral image cannot be compromised andin these cases, lossless compression is mandatory. The main goal of this thesisis to provide improved methods for the lossless compression of hyperspectral images. Both prediction- and transform-based methods are studied. Two kinds of prediction based methods are being studied. In the first method the spectra of a hyperspectral image are first clustered and and an optimized linear predictor is calculated for each cluster. In the second prediction method linear prediction coefficients are not fixed but are recalculated for each pixel. A parallel implementation of the above-mentioned linear prediction method is also presented. Also,two transform-based methods are being presented. Vector Quantization (VQ) was used together with a new coding of the residual image. In addition we have developed a new back end for a compression method utilizing Principal Component Analysis (PCA) and Integer Wavelet Transform (IWT). The performance of the compressionmethods are compared to that of other compression methods. The results show that the proposed linear prediction methods outperform the previous methods. In addition, a novel fast exact nearest-neighbor search method is developed. The search method is used to speed up the Linde-Buzo-Gray (LBG) clustering method.