Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement

The relationship between changes in retinal vessel morphology and the onset and progression of diseases such as diabetes, hypertension and retinopathy of prematurity (ROP) has been the subject of several large scale clinical studies. However, the difficulty of quantifying changes in retinal vessels in a sufficiently fast, accurate and repeatable manner has restricted the application of the insights gleaned from these studies to clinical practice. This paper presents a novel algorithm for the efficient detection and measurement of retinal vessels, which is general enough that it can be applied to both low and high resolution fundus photographs and fluorescein angiograms upon the adjustment of only a few intuitive parameters. Firstly, we describe the simple vessel segmentation strategy, formulated in the language of wavelets, that is used for fast vessel detection. When validated using a publicly available database of retinal images, this segmentation achieves a true positive rate of 70.27%, false positive rate of 2.83%, and accuracy score of 0.9371. Vessel edges are then more precisely localised using image profiles computed perpendicularly across a spline fit of each detected vessel centreline, so that both local and global changes in vessel diameter can be readily quantified. Using a second image database, we show that the diameters output by our algorithm display good agreement with the manual measurements made by three independent observers. We conclude that the improved speed and generality offered by our algorithm are achieved without sacrificing accuracy. The algorithm is implemented in MATLAB along with a graphical user interface, and we have made the source code freely available. 

Automatic detection and classification of football players

Color segmentation of images usually requires a manual selection and classification of samples to train the system. This paper presents an automatic system that performs these tasks without the need of a long training, providing a useful tool to detect and identify figures. In real situations, it is necessary to repeat the training process if light conditions change, or if, in the same scenario, the colors of the figures and the background may have changed, being useful a fast training method. A direct application of this method is the detection and identification of football players.

2D silhouette and 3D skeletal models for human detection and tracking

In this paper we propose a statistical model for detection and tracking of human silhouette and the corresponding 3D skeletal structure in gait sequences. We follow a point distribution model (PDM) approach using a Principal Component Analysis (PCA). The problem of non-lineal PCA is partially resolved by applying a different PDM depending of pose estimation; frontal, lateral and diagonal, estimated by Fisher's linear discriminant. Additionally, the fitting is carried out by selecting the closest allowable shape from the training set by means of a nearest neighbor classifier. To improve the performance of the model we develop a human gait analysis to take into account temporal dynamic to track the human body. The incorporation of temporal constraints on the model increase reliability and robustness.

Human aflatoxin albumin adducts quantitatively compared by ELISA, HPLC with fluorescence detection, and HPLC with isotope dilution mass spectrometry

Essential to the conduct of epidemiologic studies examining aflatoxin exposure and the risk of heptocellular carcinoma, impaired growth, and acute toxicity has been the development of quantitative biomarkers of exposure to aflatoxins, particularly aflatoxin B-1. In this study, identical serum sample sets were analyzed for aflatoxin-albumin adducts by ELISA, high-performance liquid chromatography (HPLC) with fluorescence detection (HPLC-f), and HPLC with isotope dilution mass spectrometry (IDMS). The human samples analyzed were from an acute aflatoxicosis outbreak in Kenya in 2004 (n = 102) and the measured values ranged from 0.018 to 67.0, nondetectable to 13.6, and 0.002 to 17.7 ng/mg albumin for the respective methods. The Deming regression slopes for the HPLC-f and ELISA concentrations as a function of the IDMS concentrations were 0.71 (r(2) = 0.95) and 3.3 (r(2) = 0.96), respectively. When the samples were classified as cases or controls, based on clinical diagnosis, all methods were predictive of outcome (P < 0.01). Further, to evaluate assay precision, duplicate samples were prepared at three levels by dilution of an exposed human sample and were analyzed on three separate days. Excluding one assay value by ELISA and one assay by HPLC-f, the overall relative SD were 8.7%, 10.5%, and 9.4% for IDMS, HPLC-f, and ELISA, respectively. IDMS was the most sensitive technique and HPLC-f was the least sensitive method. Overall, this study shows an excellent correlation between three independent methodologies conducted in different laboratories and supports the validation of these technologies for assessment of human exposure to this environmental toxin and carcinogen.

Multiplex Solid-Phase PCR for Rapid Detection and Identification of Salmonella spp. at Sub-species

This study presents a solid-phase PCR (SP-PCR) for rapid detection, identification, and sub-typing of various Salmonella species, the major food-borne cause of salmonellosis. The target DNA is firstly amplified with PCR primers (one primer is labeled with fluorophores) in the liquid phase. Simultaneously on the solid phase, the amplified PCR amplicons interact with the nested DNA probes immobilized on the solid substrate as an array. If the immobilized probes match the sequence of the DNA templates they are extended by the polymerase and serve as template for the second strand elongation primed by the liquid phase primer thus generating new templates for the SP-PCR. After the reaction, PCR products labeled with fluorophores remain attached to the substrate and can be visualized directly by fluorescence readout devices. Using this method, S. enteritidis, S. typhimurium and S. dublin can be detected at the same time. The method offers several advantages over conventional multiplex PCR: less competition between different primer pairs thus increasing multiplexing capability, only single wavelength optical readout needed for the multiplexing detection, and less time-consuming owing to reduction of the post-PCR gel electrophoresis. The method will be useful for development of point-of-care devices for rapid detection and identification of Salmonella spp. A solid-phase PCR for rapid detection and identification of S. enteritidis, S. typhimurium and S. dublin is developed. The method offers advantages such as better multiplexing capability, only single wavelength optical readout needed, and less time-consuming.

Detection and partial characterization of human B cell colony stimulating activity in synovial fluids of patients with rheumatoid arthritis

The joint fluids of 37 patients with rheumatoid arthritis, eight patients with traumatic injuries to their joints, two patients with Reiter's syndrome and three patients with psoriatic arthritis were tested for the presence of B cell colony stimulating activity (B cell CSA). B cell CSA was found in all of the joint fluids from the patients with rheumatoid arthritis but in none of the joint fluids from patients with traumatic injuries to their joints or in the joint fluids from the patients with Reiter's syndrome. A trace of B cell CSA was found in the joint fluid of one of the three patients with psoriatic arthritis. There was a positive correlation (r = 0.796) between the amount of rheumatoid factor present in the joint fluids and the titre of B cell CSA. This correlation was highly significant (P less than 0.001). The B cell CSA was localized to component(s) with molecular weight ranges 115-129 kD and 64-72 kD and an isoelectric point of 6.8. Its activity was sensitive to reduction with 2-mercaptoethanol and to the oxidising action of potassium periodate.

Whole Slide Image Cytometry: a Novel Method for the Detection and Quantification of Abnormal DNA Contents in Barrett’s Oesophagus

Background: Barrett's oesophagus (BO) is a well recognized precursor of the majority of cases of oesophageal adenocarcinoma (OAC). Endoscopic surveillance of BO patients is frequently undertaken in an attempt to detect early OAC, high grade dysplasia (HGD) or low grade dysplasia (LGD). However histological interpretation and grading of dysplasia is subjective and poorly reproducible. The alternative flow cytometry and cytology-preparation image cytometry techniques require large amounts of tissue and specialist expertise which are not widely available for frontline health care.
Methods: This study has combined whole slide imaging with DNA image cytometry, to provide a novel method for the detection and quantification of abnormal DNA contents. 20 cases were evaluated, including 8 Barrett's specialised intestinal metaplasia (SIM), 6 LGD and 6 HGD. Feulgen stained oesophageal sections (1µm thickness) were digitally scanned in their entirety and evaluated to select regions of interests and abnormalities. Barrett’s mucosa was then interactively chosen for automatic nuclei segmentation where irrelevant cell types are ignored. The combined DNA content histogram for all selected image regions was then obtained. In addition, histogram measurements, including 5c exceeding ratio (xER-5C), 2c deviation index (2cDI) and DNA grade of malignancy (DNA-MG), were computed.
Results: The histogram measurements, xER-5C, 2cDI and DNA-MG, were shown to be effective in differentiating SIM from HGD, SIM from LGD, and LGD from HGD. All three measurements discriminated SIM from HGD cases successfully with statistical significance (pxER-5C=0.0041, p2cDI=0.0151 and pDNA-MG=0.0057). Statistical significance is also achieved differentiating SIM from LGD samples with pxER-5C=0.0019, p2cDI=0.0023 and pDNA-MG=0.0030. Furthermore the differences between LGD and HGD cases are statistical significant (pxER-5C=0.0289, p2cDI=0.0486 and pDNA-MG=0.0384).
Conclusion: Whole slide image cytometry is a novel and effective method for the detection and quantification of abnormal DNA content in BO. Compared to manual histological review, this proposed method is more objective and reproducible. Compared to flow cytometry and cytology-preparation image cytometry, the current method is low cost, simple to use and only requires a single 1µm tissue section. Whole slide image cytometry could assist the routine clinical diagnosis of dysplasia in BO, which is relevant for future progression risk to OAC.

Automated detection and measurement of isolated retinal arterioles by a combination of edge enhancement and cost analysis

Pressure myography studies have played a crucial role in our understanding of vascular physiology and pathophysiology. Such studies depend upon the reliable measurement of changes in the diameter of isolated vessel segments over time. Although several software packages are available to carry out such measurements on small arteries and veins, no such software exists to study smaller vessels (<50 µm in diameter). We provide here a new, freely available open-source algorithm, MyoTracker, to measure and track changes in the diameter of small isolated retinal arterioles. The program has been developed as an ImageJ plug-in and uses a combination of cost analysis and edge enhancement to detect the vessel walls. In tests performed on a dataset of 102 images, automatic measurements were found to be comparable to those of manual ones. The program was also able to track both fast and slow constrictions and dilations during intraluminal pressure changes and following application of several drugs. Variability in automated measurements during analysis of videos and processing times were also investigated and are reported. MyoTracker is a new software to assist during pressure myography experiments on small isolated retinal arterioles. It provides fast and accurate measurements with low levels of noise and works with both individual images and videos. Although the program was developed to work with small arterioles, it is also capable of tracking the walls of other types of microvessels, including venules and capillaries. It also works well with larger arteries, and therefore may provide an alternative to other packages developed for larger vessels when its features are considered advantageous.

Device-Free Person Detection and Ranging in UWB Networks

We present a novel device-free stationary person detection and ranging method, that is applicable to ultra-wide bandwidth (UWB) networks. The method utilizes a fixed UWB infrastructure and does not require a training database of template waveforms. Instead, the method capitalizes on the fact that a human presence induces small low-frequency variations that stand out against the background signal, which is mainly affected by wideband noise. We analyze the detection probability, and validate our findings with numerical simulations and experiments with off-the-shelf UWB transceivers in an indoor environment. © 2007-2012 IEEE.