Image Thresholding Technique Based On Fuzzy Partition And Entropy Maximization

Thresholding is a commonly used technique in image segmentation because of its fast and easy application. For this reason threshold selection is an important issue. There are two general approaches to threshold selection. One approach is based on the histogram of the image while the other is based on the gray scale information located in the local small areas. The histogram of an image contains some statistical data of the grayscale or color ingredients. In this thesis, an adaptive logical thresholding method is proposed for the binarization of blueprint images first. The new method exploits the geometric features of blueprint images. This is implemented by utilizing a robust windows operation, which is based on the assumption that the objects have "e;C"e; shape in a small area. We make use of multiple window sizes in the windows operation. This not only reduces computation time but also separates effectively thin lines from wide lines. Our method can automatically determine the threshold of images. Experiments show that our method is effective for blueprint images and achieves good results over a wide range of images. Second, the fuzzy set theory, along with probability partition and maximum entropy theory, is explored to compute the threshold based on the histogram of the image. Fuzzy set theory has been widely used in many fields where the ambiguous phenomena exist since it was proposed by Zadeh in 1965. And many thresholding methods have also been developed by using this theory. The concept we are using here is called fuzzy partition. Fuzzy partition means that a histogram is parted into several groups by some fuzzy sets which represent the fuzzy membership of each group because our method is based on histogram of the image . Probability partition is associated with fuzzy partition. The probability distribution of each group is derived from the fuzzy partition. Entropy which originates from thermodynamic theory is introduced into communications theory as a commonly used criteria to measure the information transmitted through a channel. It is adopted by image processing as a measurement of the information contained in the processed images. Thus it is applied in our method as a criterion for selecting the optimal fuzzy sets which partition the histogram. To find the threshold, the histogram of the image is partitioned by fuzzy sets which satisfy a certain entropy restriction. The search for the best possible fuzzy sets becomes an important issue. There is no efficient method for the searching procedure. Therefore, expansion to multiple level thresholding with fuzzy partition becomes extremely time consuming or even impossible. In this thesis, the relationship between a probability partition (PP) and a fuzzy C-partition (FP) is studied. This relationship and the entropy approach are used to derive a thresholding technique to select the optimal fuzzy C-partition. The measure of the selection quality is the entropy function defined by the PP and FP. A necessary condition of the entropy function arriving at a maximum is derived. Based on this condition, an efficient search procedure for two-level thresholding is derived, which makes the search so efficient that extension to multilevel thresholding becomes possible. A novel fuzzy membership function is proposed in three-level thresholding which produces a better result because a new relationship among the fuzzy membership functions is presented. This new relationship gives more flexibility in the search for the optimal fuzzy sets, although it also increases the complication in the search for the fuzzy sets in multi-level thresholding. This complication is solved by a new method called the "e;Onion-Peeling"e; method. Because the relationship between the fuzzy membership functions is so complicated it is impossible to obtain the membership functions all at once. The search procedure is decomposed into several layers of three-level partitions except for the last layer which may be a two-level one. So the big problem is simplified to three-level partitions such that we can obtain the two outmost membership functions without worrying too much about the complicated intersections among the membership functions. The method is further revised for images with a dominant area of background or an object which affects the appearance of the histogram of the image. The histogram is the basis of our method as well as of many other methods. A "e;bad"e; shape of the histogram will result in a bad thresholded image. A quadtree scheme is adopted to decompose the image into homogeneous areas and heterogeneous areas. And a multi-resolution thresholding method based on quadtree and fuzzy partition is then devised to deal with these images. Extension of fuzzy partition methods to color images is also examined. An adaptive thresholding method for color images based on fuzzy partition is proposed which can determine the number of thresholding levels automatically. This thesis concludes that the "e;C"e; shape assumption and varying sizes of windows for windows operation contribute to a better segmentation of the blueprint images. The efficient search procedure for the optimal fuzzy sets in the fuzzy-2 partition of the histogram of the image accelerates the process so much that it enables the extension of it to multilevel thresholding. In three-level fuzzy partition the new relationship presentation among the three fuzzy membership functions makes more sense than the conventional assumption and, as a result, performs better. A novel method, the "e;Onion-Peeling"e; method, is devised for dealing with the complexity at the intersection among the multiple membership functions in the multilevel fuzzy partition. It decomposes the multilevel partition into the fuzzy-3 partitions and the fuzzy-2 partitions by transposing the partition space in the histogram. Thus it is efficient in multilevel thresholding. A multi-resolution method which applies the quadtree scheme to distinguish the heterogeneous areas from the homogeneous areas is designed for the images with large homogeneous areas which usually distorts the histogram of the image. The new histogram based on only the heterogeneous area is adopted for partition and outperforms the old one. While validity checks filter out the fragmented points which are only a small portion of the whole image. Thus it gives good thresholded images for human face images

Extracellular Matrix Stiffness and Composition Regulate the Myofibroblast Differentiation of Vaginal Fibroblasts

Fibroblast to myofibroblast differentiation is a key feature of wound-healing in soft tissues, including the vagina. Vaginal fibroblasts maintain the integrity of the vaginal wall tissues, essential to keep pelvic organs in place and avoid pelvic organ prolapse (POP). The micro-environment of vaginal tissues in POP patients is stiffer and has different extracellular matrix (ECM) composition than healthy vaginal tissues. In this study, we employed a series of matrices with known stiffnesses, as well as vaginal ECMs, in combination with vaginal fibroblasts from POP and healthy tissues to investigate how matrix stiffness and composition regulate myofibroblast differentiation in vaginal fibroblasts. Stiffness was positively correlated to production of α-smooth muscle actin (α-SMA). Vaginal ECMs induced myofibroblast differentiation as both α-SMA and collagen gene expressions were increased. This differentiation was more pronounced in cells seeded on POP-ECMs that were stiffer than those derived from healthy tissues and had higher collagen and elastin protein content. We showed that stiffness and ECM content regulate vaginal myofibroblast differentiation. We provide preliminary evidence that vaginal fibroblasts might recognize POP-ECMs as scar tissues that need to be remodeled. This is fundamentally important for tissue repair, and provides a rational basis for POP disease modelling and therapeutic innovations in vaginal reconstruction

Diagnostic DNA Methylation Biomarkers for Renal Cell Carcinoma:A Systematic Review

CONTEXT: The 5-yr survival of early-stage renal cell carcinoma (RCC) is approximately 93%, but once metastasised, the 5-yr survival plummets to 12%, indicating that early RCC detection is crucial to improvement in survival. DNA methylation biomarkers have been suggested to be of potential diagnostic value; however, their current state of clinical translation is unclear and a comprehensive overview is lacking. OBJECTIVE: To systematically review and summarise all literature regarding diagnostic DNA methylation biomarkers for RCC. EVIDENCE ACQUISITION: We performed a systematic literature review of PubMed, EMBASE, Medline, and Google Scholar up to January 2019, according to the Preferred Reporting Items for Systematic Review and Meta-Analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines. Included studies were scored according to the Standards for Reporting of Diagnostic Accuracy Studies (STARD) criteria. Forest plots were generated to summarise diagnostic performance of all biomarkers. Level of evidence (LoE) and potential risk of bias were determined for all included studies. EVIDENCE SYNTHESIS: After selection, 19 articles reporting on 44 diagnostic DNA methylation biomarkers and 11 multimarker panels were included; however, only 15 biomarkers were independently validated. STARD scores varied from 4 to 13 out of 23 points, with a median of 10 points. Large variation in subgroups, methods, and primer locations was observed. None of the reported biomarkers exceeded LoE III, and the majority of studies reported inadequately. CONCLUSIONS: None of the reported biomarkers exceeded LoE III, indicating their limited clinical utility. Moreover, study reproducibility and further development of these RCC biomarkers are greatly hampered by inadequate reporting. PATIENT SUMMARY: In this report, we reviewed whether specific biomarkers could be used to diagnose the most common form of kidney cancer. We conclude that due to limited evidence and reporting inconsistencies, none of these biomarkers can be used in clinical practice, and further development towards clinical use is hindered

Spectral analysis and resolving spatial ambiguities in human sound localization

This dissertation provides an overview of my research over the last five years into the spectral analysis involved in human sound localization. The work involved conducting psychophysical tests of human auditory localization performance and then applying analytical techniques to analyze and explain the data. It is a fundamental thesis of this work that human auditory localization response directions are primarily driven by the auditory localization cues associated with the acoustic filtering properties of the external auditory periphery, i.e., the head, torso, shoulder, neck, and external ears. This work can be considered as composed of three parts. In the first part of this work, I compared the auditory localization performance of a human subject and a time-delay neural network model under three sound conditions: broadband, high-pass, and low-pass. A “black-box” modeling paradigm was applied. The modeling results indicated that training the network to localize sounds of varying center-frequency and bandwidth could degrade localization performance results in a manner demonstrating some similarity to human auditory localization performance. As the data collected during the network modeling showed that humans demonstrate striking localization errors when tested using bandlimited sound stimuli, the second part of this work focused on human sound localization of bandpass filtered noise stimuli. Localization data was collected from 5 subjects and for 7 sound conditions: 300 Hz to 5 kHz, 300 Hz to 7 kHz, 300 Hz to 10 kHz, 300 Hz to 14 kHz, 3 to 8 kHz, 4 to 9 kHz, and 7 to 14 kHz. The localization results were analyzed using the method of cue similarity indices developed by Middlebrooks (1992). The data indicated that the energy level in relatively wide frequency bands could be driving the localization response directions, just as in Butler’s covert peak area model (see Butler and Musicant, 1993). The question was then raised as to whether the energy levels in the various frequency bands, as described above, are most likely analyzed by the human auditory localization system on a monaural or an interaural basis. In the third part of this work, an experiment was conducted using virtual auditory space sound stimuli in which the monaural spectral cues for auditory localization were disrupted, but the interaural spectral difference cue was preserved. The results from this work showed that the human auditory localization system relies primarily on a monaural analysis of spectral shape information for its discrimination of directions on the cone of confusion. The work described in the three parts lead to the suggestion that a spectral contrast model based on overlapping frequency bands of varying bandwidth and perhaps multiple frequency scales can provide a reasonable algorithm for explaining much of the current psychophysical and neurophysiological data related to human auditory localization

Elevated CAIX Expression is Associated with an Increased Risk of Distant Failure in Early-Stage Cervical Cancer

Tumor hypoxia is associated with adverse outcome in many malignancies. The goal of this study was to determine if elevated expression of carbonic anhydrase IX (CAIX), a biomarker of hypoxia, predicts for recurrence in early-stage cervical cancer. The charts of all patients with early-stage cervical cancer, primarily FIGO IB, treated by radical hysterectomy at our institution from 1988–2001 were reviewed. Adequate pathologic specimens from patients who recurred or who had at least three years follow-up and remained disease-free were stained for CAIX. An immunohistochemical score (IHC) was generated from the extent/intensity of staining. Outcome, as measured by freedom from recurrence (FFR), distant metastases (FFDM) and local recurrence (FFLR), was analyzed as a function of age, IHC, lymph node status (LN) and histology. Forty-two relapsing patients and 76 non-relapsing patients were evaluated. In univariate analysis, +LN, though not IHC or histology, was a significant predictor of any recurrence. Both +LN and higher IHC were associated with decreased FFDM but not FFLR. Patients with both +LN and elevated IHC more frequently exhibited distant metastases as first site of failure (5-year FFDM 50%) than patients with only +LN, elevated IHC or neither feature (70, 85 and 95%, respectively, p = 0.0004). In multivariable analysis, only +LN was significantly associated with poorer FFDM (hazard ratio 4.6, p = 0.0015) though there was a strong trend with elevated CAIX expression (p = 0.069). Elevated CAIX expression is associated with more frequent distant metastases in early-stage cervical cancer, suggesting that patients with this characteristic may benefit from more aggressive treatment

GATA transcription factors in testicular adrenal rest tumours

Testicular adrenal rest tumours (TARTs) are benign adrenal-like testicular tumours that frequently occur in male patients with congenital adrenal hyperplasia. Recently, GATA transcription factors have been linked to the development of TARTs in mice. The aim of our study was to determine GATA expression in human TARTs and other steroidogenic tissues. We determined GATA expression in TARTs (n = 16), Leydig cell tumours (LCTs; n = 7), adrenal (foetal (n = 6) + adult (n = 10)) and testis (foetal (n = 13) + adult (n = 8)). We found testis-like GATA4, and adrenal-like GATA3 and GATA6 gene expressions by qPCR in human TARTs, indicating mixed testicular and adrenal characteristics of TARTs. Currently, no marker is available to discriminate TARTs from LCTs, leading to misdiagnosis and incorrect treatment. GATA3 and GATA6 mRNAs exhibited excellent discriminative power (area under the curve of 0.908 and 0.816, respectively), while immunohistochemistry did not. GATA genes contain several CREB-binding sites and incubation with 0.1 mM dibutyryl cAMP for 4 h stimulated GATA3, GATA4 and GATA6 expressions in a human foetal testis cell line (hs181.tes). Incubation of adrenocortical cells (H295RA) with ACTH, however, did not induce GATA expression in vitro Although ACTH did not dysregulate GATA expression in the only human ACTH-sensitive in vitro model available, our results do suggest that aberrant expression of GATA transcription factors in human TARTs might be involved in TART formation