Feature detection algorithms in computed images

The problem of sensing a medium by several sensors and retrieving interesting features is a very general one. The basic framework of the problem is generally the same for applications from MRI, tomography, Radar SAR imaging to subsurface imaging, even though the data acquisition processes, sensing geometries and sensed properties are different. In this thesis we introduced a new perspective to the problem of remote sensing and information retrieval by studying the problem of subsurface imaging using GPR and seismic sensors. We have shown that if the sensed medium is sparse in some domain then it can be imaged using many fewer measurements than required by the standard methods. This leads to much lower data acquisition times and better images representing the medium. We have used the ideas from Compressive Sensing, which show that a small number of random measurements about a signal is sufficient to completely characterize it, if the signal is sparse or compressible in some domain. Although we have applied our ideas to the subsurface imaging problem, our results are general and can be extended to other remote sensing applications. A second objective in remote sensing is information retrieval which involves searching for important features in the computed image of the medium. In this thesis we focus on detecting buried structures like pipes, and tunnels in computed GPR or seismic images. The problem of finding these structures in high clutter and noise conditions, and finding them faster than the standard shape detecting methods like the Hough transform is analyzed. One of the most important contributions of this thesis is, where the sensing and the information retrieval stages are unified in a single framework using compressive sensing. Instead of taking lots of standard measurements to compute the image of the medium and search the necessary information in the computed image, a much smaller number of measurements as random projections are taken. The data acquisition and information retrieval stages are unified by using a data model dictionary that connects the information to the sensor data.Ph.D.Committee Chair: McClellan, James H.; Committee Member: Romberg, Justin K.; Committee Member: Scott, Waymond R. Jr.; Committee Member: Vela, Patricio A.; Committee Member: Vidakovic, Bran

The effectiveness of Sufi music for mental health outcomes. A systematic review and meta-analysis of 21 randomised trials.

BACKGROUND: There is some evidence that Sufi music therapy might improve physical and mental well-being; however, no systematic review or meta-analysis has pooled and critiqued the evidence. The aim of this systematic review was to evaluate the effects of Sufi music therapy on mental health outcomes. METHODS: We searched Medline, PsycINFO, the Web of Science, Science Direct, PsycARTICLES, Cochrane Library, SCOPUS, CINAHL Plus, AMED, and ULAKBIM databases, and the reference lists of the studies found. Papers published in academic peer-reviewed journals were included, as well as from other sources such as chapters in edited books, the grey literature, or conference presentations. Articles published up to March 2020 in Turkish and English were included. Our primary outcome of interest was anxiety and secondary outcomes of interest were other mental health outcomes such as depression. To assess the methodological quality of the articles, the Cochrane Risk of Bias Tool was used. The quality of evidence was assessed using the GRADEpro GDT system. RESULTS: This search yielded 21 clinical trials that were eligible for inclusion. A meta-analysis, using a random effects model, of 18 randomised controlled trials involving 1454 participants showed that Sufi music therapy with makams, compared with treatment as usual (TAU) or a no-music control group, reduced symptoms of anxiety in the short term in patients undergoing an operation or treatments such as chemotherapy or haemodialysis (standardised mean difference SMD= -1.15, 95% CI, -1.64 to -0.65; very low-quality evidence). The evidence of Sufi music with makam's effect on anxiety is rated as very low. Qualitative synthesis of secondary outcomes revealed significant effects for depression, positive symptoms in schizophrenia, stress, which however were based on fewer studies. Trials were of moderate methodological quality, and there was significant heterogeneity across the studies. CONCLUSION: Sufi music may reduce anxiety of patients undergoing medical procedures like haemodialysis, coronary artery surgery, angiography, colonoscopy, bone marrow aspiration and biopsy procedures. Evidence from single studies suggests effects on depression and stress as well. However, due to methodological limitations of the studies, further, higher quality studies are required in other cultures

Performance Analysis of Compressive-Sensing-Based Through-the-Wall Imaging with Effect of Unknown Parameters

Compressive sensing (CS) has been shown to be a useful tool for subsurface or through-the-wall imaging (TWI) using ground penetrating radar (GPR). It has been used to decrease both time/frequency or spatial measurements and generate high-resolution images. Although current works apply CS directly to TWI, questions on the required number of measurements for a sparsity level, measurement strategy to subsample in frequency and space, or imaging performance in varying noise levels and limits on CS range resolution performance still needs to be answered. In addition current CS-based imaging methods are based on two basic assumptions; targets are point like and positioned at only discrete grid locations and wall thickness and its dielectric constant are perfectly known. However, these assumptions are not usually valid in most TWI applications. This work extends the theory of CS-based radar imaging developed for subsurface imaging to TWI and outlines the performance of the proposed imaging for the above-mentioned questions using numerical simulations. The effect of unknown parameters on the imaging performance is analyzed, and it is observed that off-the-grid point targets and big modeling errors decreases the performance of CS imaging

Genome-wide SNP discovery and QTL mapping for fruit quality traits in inbred backcross lines (IBLs) of solanum pimpinellifolium using genotyping by sequencing

Background: Solanum pimpinellifolium has high breeding potential for fruit quality traits and has been used as a donor in tomato breeding programs. Unlocking the genetic potential of S. pimpinellifolium requires high-throughput polymorphism identification protocols for QTL mapping and introgression of favourable alleles into cultivated tomato by both positive and background selection. Results: In this study we identified SNP loci using a genotyping by sequencing (GBS) approach in an IBL mapping population derived from the cross between a high yielding fresh market tomato and S. pimpinellifolium (LA1589) as the recurrent and donor parents, respectively. A total of 120,983,088 reads were generated by the Illumina HiSeq next-generation sequencing platform. From these reads 448,539 sequence tags were generated. A majority of the sequence tags (84.4%) were uniquely aligned to the tomato genome. A total of 3.125 unique SNP loci were identified as a result of tag alignment to the genome assembly and were used in QTL analysis of 11 fruit quality traits. As a result, 37 QTLs were identified. S. pimpinellifolium contributed favourable alleles for 16 QTLs (43.2%), thus confirming the high breeding potential of this wild species. Conclusions: The present work introduced a set of SNPs at sufficiently high density for QTL mapping in populations derived from S. pimpinellifolium (LA1589). Moreover, this study demonstrated the high efficiency of the GBS approach for SNP identification, genotyping and QTL mapping in an interspecific tomato population.Scientific and Technological Research Council of Turkey (TUBITAK 114Z116

Compressive wireless arrays for bearing estimation

Joint processing of sensor array outputs improves the performance of parameter estimation and hypothesis testing problems beyond the slim of the individual sensor processing results. When the sensors have high data sampling rates, arrays are tethered, creating a disadvantage for their deployment and also limiting their aperture size. In this paper, we develop the signal processing algorithms for randomly deployable wireless sensor arrays that are severely constrained in communication bandwidth. We focus on the acoustic bearing estimation problem and show that when the target bearings are modeled as a sparse vector in the angle space, low dimensional random projections of the microphone signals can be used to determine multiple source bearings by solving an l(1)-norm minimization problem. Field data results are shown where only 10 bits of information is passed from each microphone to estimate multiple target bearings

Papillary microcarcinomas of the thyroid gland and immunohistochemical analysis of expression of p53 protein in papillary microcarcinomas

BACKGROUND: Thyroid papillary microcarcinoma (TPM) is defined according to WHO criteria as a thyroid tumor smaller than 1–1.5 cm. TPMs are encountered in 0.5–35.6 % of autopsies or surgical specimens where carcinoma had been unsuspected. The purpose of the present study was to evaluate patients who had TPMs in terms of clinical findings, histopathological features and immunohistochemical evidence of expression of the tumor suppressor gene p53. METHODS: A total of 44 patients with TPMs less than 1.0 cm in diameter were included in the study. The patients were evaluated clinically and the tumors were evaluated in terms of their histopathological and immunohistochemical features, including expression of p53. RESULTS: The female/male ratio was 2.8/1, and the median age at time of diagnosis was 49 years (range 20–71 years). The maximum diameter of the smallest focus was 0.1 mm, and that of the largest was 10 mm microscopically. The mean diameter of all tumors was 5.7 mm. There was no correlation between tumor size and age or gender. Of the TPMs, 72 % were found in the right lobe, 24 % in the left lobe and 4 % in the isthmus. Fine-needle aspiration biopsy provided the diagnosis of TPM in only 43.2 % of the patients. All patients were treated with surgery, with 20 undergoing conservative surgery, i.e. lobectomy or isthmusectomy, and 24 undergoing total thyroidectomy. Frozen section provided the diagnosis of TPM in only 56.8 % of the patients. We found lymphocytic thyroiditis in 13.6% of patients, follicular variants in 11.9%, capsular invasion in 26.8%, lymph node involvement in 11.9%, soft tissue metastases in the neck in 12.1% and multifocality in 31.7 %, and none of these were related to age or gender (p > 0.05). No distant metastases were observed during approximately 10 years of follow up. We found p53 positivity in 34.5 % of TPM tumors. However, p53 expression was not statistically related to age or gender. CONCLUSION: Our findings imply that TPMs may not be entirely innocent since they are associated with signs of poor prognosis such as capsular invasion, multifocal presentation, lymph node involvement and p53 positivity. Therefore, TPMs should be evaluated and followed like classical papillary cancers