REVIEW - A reference data set for retinal vessel profiles

This paper describes REVIEW, a new retinal vessel reference dataset. This dataset includes 16 images with 193 vessel segments, demonstrating a variety of pathologies and vessel types. The vessel edges are marked by three observers using a special drawing tool. The paper also describes the algorithm used to process these segments to produce vessel profiles, against which vessel width measurement algorithms can be assessed. Recommendations are given for use of the dataset in performance assessment. REVIEW can be downloaded from http://ReviewDB.lincoln.ac.uk

Retinal vessel segmentation using Gabor Filter and Textons

This paper presents a retinal vessel segmentation method that is inspired by the human visual system and uses a Gabor filter bank. Machine learning is used to optimize the filter parameters for retinal vessel extraction. The filter responses are represented as textons and this allows the corresponding membership functions to be used as the framework for learning vessel and non-vessel classes. Then, vessel texton memberships are used to generate segmentation results. We evaluate our method using the publicly available DRIVE database. It achieves competitive performance (sensitivity=0.7673, specificity=0.9602, accuracy=0.9430) compared to other recently published work. These figures are particularly interesting as our filter bank is quite generic and only includes Gabor responses. Our experimental results also show that the performance, in terms of sensitivity, is superior to other methods

Ship design with the human factor: evacuation and normal operations modelling in the ship design process

This thesis addresses the modelling of human factors and how they can impact ship design. Two different but related applications areas are considered; passenger ship evacuation analysis and naval vessel normal operations and evacuation analysis. In the first instance, this thesis investigates the impact of the current regulatory specified passenger response time distributions upon evacuation analysis and then recommends a more realistic passenger response time distribution which should be implemented when performing an evacuation analysis of a passenger RO-RO vessel. This realistic passenger response time distribution is based upon the results of sea trials. The results of this analysis have been adopted by the IMO and form part of the new guideline document, IMO MSC 1238. In addition, this thesis addresses the analysis of the human factors’ performance of a naval vessel. Naval vessels are built primarily for undertaking assigned missions in times of war and conflict. While the safety of those on board is important, the ability of the vessel to function and complete its assigned mission is of paramount importance. This thesis utilises an evacuation model, maritimeEXODUS, which was extended to incorporate the functionality of modelling non-evacuation scenarios, to assess the human factors’ performance of a naval vessel during both normal operations and evacuation scenarios. This thesis develops a methodology for simultaneously assessing the human factors’ performance of both a range of normal operation scenarios and evacuation scenario on board a naval vessel. The methodology, called the Human Performance Metric (HPM), is discriminating, diagnostic, systematic, transparent and reproducible in nature. This thesis then implements the HPM methodology into the early stages of the design cycle for a new naval vessel. The thesis presents the software modifications required to implement the methodology in to the design cycle as well as presenting a demonstration of the new system

Development Of A Semi-Swath Craft For Malaysian Waters

Small Waterplane Area Twin Hull (SWATH) and Catamaran vessels are known to have more stable platform as compared to mono-hulls. A further advantage of SWATH as compared to Catamaran is its smaller waterplane area that provides better seakeeping qualities. However, the significant drawback of the SWATH vessel is when encountering head-sea at high forward speed. Due to its low stiffness, it has a tendency for large pitch motions. Consequently, this may lead to excessive trim or even deck wetness. This phenomenon will not only degrade the comfortability but also results in structural damage with greater safety risks. In this research a modified SWATH design is proposed. The proposed design concept represents a combination of Catamaran and SWATH vessel hull features that will lead to reduce in bow-diving but still maintains good seakeeping capabilities. This is then called the Semi- SWATH vessel. In addition, the full-design of this vessel has been equipped by fixed fore fins and controllable aft fins attached on each lower hull. In the development of controllable aft fins, the PID controller system was applied to obtain an optimal vessel’s ride performance at speeds of 15 (medium) and 20 (high) knots. In this research work, the seakeeping performance of Semi-SWATH vessel was evaluated using time-domain simulation approach. The effect of fin stabilizer on the bare hull performance is considered. The validity of numerical evaluation was then compared with model experiments carried out in the Towing Tank at Marine Technology Laboratory, UTM. It is shown that the Semi-SWATH vessel with controllable fin stabilizer can have significantly reduction by about 42.57% of heave motion and 48.80% of pitch motion

Vessel tractography using an intensity based tensor model

In this paper, we propose a novel tubular structure segmen- tation method, which is based on an intensity-based tensor that fits to a vessel. Our model is initialized with a single seed point and it is ca- pable of capturing whole vessel tree by an automatic branch detection algorithm. The centerline of the vessel as well as its thickness is extracted. We demonstrated the performance of our algorithm on 3 complex contrast varying tubular structured synthetic datasets for quantitative validation. Additionally, extracted arteries from 10 CTA (Computed Tomography An- giography) volumes are qualitatively evaluated by a cardiologist expert’s visual scores

Measurement of retinal vessel widths from fundus images based on 2-D modeling

Changes in retinal vessel diameter are an important sign of diseases such as hypertension, arteriosclerosis and diabetes mellitus. Obtaining precise measurements of vascular widths is a critical and demanding process in automated retinal image analysis as the typical vessel is only a few pixels wide. This paper presents an algorithm to measure the vessel diameter to subpixel accuracy. The diameter measurement is based on a two-dimensional difference of Gaussian model, which is optimized to fit a two-dimensional intensity vessel segment. The performance of the method is evaluated against Brinchmann-Hansen's half height, Gregson's rectangular profile and Zhou's Gaussian model. Results from 100 sample profiles show that the presented algorithm is over 30% more precise than the compared techniques and is accurate to a third of a pixel

Determination of the hydrodynamic performance of marine propellers using fibre Bragg gratings

Downloading of the abstract is permitted for personal use only. A critical aspect in the design of marine propellers is their hydrodynamic performance which, when evaluated experimentally, requires a number of parameters to be monitored at the same time, i.e.The thrust and torque a propeller generates as well as the propeller shaft and vessel speed. In this investigation, three of those parameters are measured using Fibre Bragg Grating-based sensors, thus allowing for computationally derived performance values to be verified. For that purpose, open water tests were carried out where an instrumented propeller shaft was installed into a research vessel and measurements taken, evaluated and the results compared favorably with advanced computer-based simulations

Retinal Vessel Segmentation Using the 2-D Morlet Wavelet and Supervised Classification

We present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or non-vessel, based on the pixel's feature vector. Feature vectors are composed of the pixel's intensity and continuous two-dimensional Morlet wavelet transform responses taken at multiple scales. The Morlet wavelet is capable of tuning to specific frequencies, thus allowing noise filtering and vessel enhancement in a single step. We use a Bayesian classifier with class-conditional probability density functions (likelihoods) described as Gaussian mixtures, yielding a fast classification, while being able to model complex decision surfaces and compare its performance with the linear minimum squared error classifier. The probability distributions are estimated based on a training set of labeled pixels obtained from manual segmentations. The method's performance is evaluated on publicly available DRIVE and STARE databases of manually labeled non-mydriatic images. On the DRIVE database, it achieves an area under the receiver operating characteristic (ROC) curve of 0.9598, being slightly superior than that presented by the method of Staal et al.Comment: 9 pages, 7 figures and 1 table. Accepted for publication in IEEE Trans Med Imag; added copyright notic