A Novel Retinal Blood Vessel Segmentation Algorithm using Fuzzy segmentation

Assessment of blood vessels in retinal images is an important factor for many medical disorders. The changes in the retinal vessels due to the pathologies can be easily identified by segmenting the retinal vessels. Segmentation of retinal vessels is done to identify the early diagnosis of the disease like glaucoma, diabetic retinopathy, macular degeneration, hypertensive retinopathy and arteriosclerosis. In this paper, we propose an automatic blood vessel segmentation method. The proposed algorithm starts with the extraction of blood vessel centerline pixels. The final segmentation is obtained using an iterative region growing method that merges the binary images resulting from centerline detection part with the image resulting from fuzzy vessel segmentation part. In this proposed algorithm, the blood vessel is enhanced using modified morphological operations and the salt and pepper noises are removed from retinal images using Adaptive Fuzzy Switching Median filter. This method is applied on two publicly available databases, the DRIVE and the STARE and the experimental results obtained by using green channel images have been presented and compared with recently published methods. The results demonstrate that our algorithm is very effective method to detect retinal blood vessels.DOI:http://dx.doi.org/10.11591/ijece.v4i4.625

Two Novel Retinal Blood Vessel Segmentation Algorithms

Assessment of blood vessels in retinal images is an important factor for many medical disorders. The changes in the retinal vessels due to the pathologies can be easily identified by segmenting the retinal vessels. Segmentation of retinal vessels is done to identify the early diagnosis of the disease like glaucoma, diabetic retinopathy, macular degeneration, hypertensive retinopathy and arteriosclerosis. In this paper, we propose two automatic blood vessel segmentation methods. The first proposed algorithm starts with the extraction of blood vessel centerline pixels. The final segmentation is obtained using an iterative region growing method that merges the contents of several binary images resulting from vessel width dependent modified morphological filters on normalized retinal images. In the second proposed algorithm the blood vessel is segmented using normalized modified morphological operations and neuro fuzzy classifier. Normalized morphological operations are used to enhance the vessels and neuro fuzzy classifier is used to segment retinal blood vessels. These methods are applied on the publicly available DRIVE database and the experimental results obtained by using green channel images have been presented and their results are compared with recently published methods. The results demonstrate that our algorithms are very effective methods to detect retinal blood vessels.DOI:http://dx.doi.org/10.11591/ijece.v4i3.582

Automated Classification of Breast Cancer Stroma Maturity from Histological Images

OBJECTIVE: The tumour microenvironment plays a crucial role in regulating tumour progression by a number of different mechanisms, in particular the remodelling of collagen fibres in tumour-associated stroma, which has been reported to be related to patient survival. The underlying motivation of this work is that remodelling of collagen fibres gives rise to observable patterns in Hematoxylin and Eosin (H&E) stained slides from clinical cases of invasive breast carcinoma that the pathologist can label as mature or immature stroma. The aim of this paper is to categorise and automatically classify stromal regions according to their maturity and show that this classification agrees with that of skilled observers, hence providing a repeatable and quantitative measure for prognostic studies. METHODS: We use multi-scale Basic Image Features (BIF) and Local Binary Patterns (LBP), in combination with a random decision trees classifier for classification of breast cancer stroma regions-ofinterest (ROI). RESULTS: We present results from a cohort of 55 patients with analysis of 169 ROI. Our multi-scale approach achieved a classification accuracy of 84%. CONCLUSION: This work demonstrates the ability of texture-based image analysis to differentiate breast cancer stroma maturity in clinically acquired H&E stained slides at least as well as skilled observers

Implementasi Pengklasifikasi Segmen Vaskular Retina Mata Dengan Metode M-Medios Multivariat

Neovaskularisasi adalah berkembangnya pembuluh darah baru di dalam mata. Pembuluh darah ini merupakan pembuluh darah yang abnormal, memiliki dinding pembuluh yang tipis, lemah, dan mudah pecah. Neovaskularisasi dapat terbentuk pada berbagai lokasi di dalam mata termasuk pada retina, sehingga citra retina dapat digunakan untuk mendeteksi neovaskularisasi secara otomatis. Pendeteksian dilakukan dengan melakukan klasifikasi terhadap segmen vaskular retina mata sebagai segmen vaskular normal atau abnormal. Tugas akhir ini mengimplementasikan salah satu metode pengklasifikasi yang dapat digunakan untuk klasifikasi segmen vaskular retina yaitu m-Mediods multivariat. Metode m-Mediods multivariat terdiri dari dua tahap. Tahap pertama adalah perbaikan ruang fitur menggunakan Local Fisher Discriminant Analysis. Tahap kedua merupakan tahap klasifikasi dengan metode Learning Vector Quantization. Sebelum dilakukan klasifikasi, terlebih dahulu dilakukan praproses dengan metode masking untuk memisahkan antara latar belakang gambar dan objek retina. Selanjutnya dilakukan segmentasi pembuluh darah menggunakan transformasi wavelet yaitu dengan Isotropic Undecimated Wavelet Transform. Tahap awal sebelum klasifikasi adalah ekstraksi ciri untuk menghasilkan vektor fitur yang digunakan sebagai pembeda segmen vaskular normal dan abnormal. Sebelum akhirnya dilakukan klasifikasi segmen vaskular dengan metode m-Mediods multivariat. Hasil uji coba dari hasil segmentasi vaskular dari citra retina pada basis data DRIVE menghasilkan nilai akurasi mencapai 95,04% dengan perbandingan citra ground truth. Sedangkan hasil klasifikasi segmen vaskular normal dan abnormal dengan citra retina dari basis data STARE menggunakan metode m-Mediods multivariat menunjukkan akurasi terbaik sebesar 96.2%. Sehingga dapat disimpulkan bahwa metode segmentasi vaskular retina dan klasifikasi segmen vaskular retina yang digunakan pada Tugas akhir ini mampu melakukan segmentasi dan klasifikasi dengan baik. ============================================================================================================================= Neovascularization is development of new blood vessels in the eyes. These new blood vessels are abnormal blood vessels, have the vessel walls are thin, weak, and easily broken. Neovascularization can be formed at various locations within the eyes including the retina, hence the retinal image can be used to detect neovascularization. Detection can be done by classifying retinal vascular segments as a normal or an abnormal vascular segment. The final project is to implement one of the methods classifiers that can be used for classification of retinal vascular segments namely m-Mediods multivariate. M-Mediods multivariate method consists of two stages. The first stage is the improvement feature space using local fisher discriminant analysis. The second stage is the stage of classification with learning vector quantization method. Before the classification, preprocessing is done by masking method to separate the object of the retina from the background image. Vascular segmentation is then performed using the wavelet transform namely undecimated isotropic wavelet transform. The initial phase of classification is feature extraction to produce a feature vector which is used to distinguish normal and abnormal vascular segment. Finally classification of vascular segments is done using m-Mediods multivariate methods. The results of the evaluation of vascular segmentation with retinal image from DRIVE database generate the accuracy value of 95.04% with ground truth image comparison. While the results of the classification of normal and abnormal vascular segments by retinal image from STARE database using multivariate m- Mediods methods shows the best accuracy of 96.2%. Therefor it can be concluded that the method used for retinal vascular segmentation and retinal vascular segments classification in this final project is reliable for segmentation and classification

Тhe benefits of an additional practice in descriptive geometry course: non obligatory workshop at the Faculty of civil engineering in Belgrade

At the Faculty of Civil Engineering in Belgrade, in the Descriptive geometry (DG) course, non-obligatory workshops named “facultative task” are held for the three generations of freshman students with the aim to give students the opportunity to get higher final grade on the exam. The content of this workshop was a creative task, performed by a group of three students, offering free choice of a topic, i.e. the geometric structure associated with some real or imagery architectural/art-work object. After the workshops a questionnaire (composed by the professors at the course) is given to the students, in order to get their response on teaching/learning materials for the DG course and the workshop. During the workshop students performed one of the common tests for testing spatial abilities, named “paper folding". Based on the results of the questionnairethe investigation of the linkages between:students’ final achievements and spatial abilities, as well as students’ expectations of their performance on the exam, and how the students’ capacity to correctly estimate their grades were associated with expected and final grades, is provided. The goal was to give an evidence that a creative work, performed by a small group of students and self-assessment of their performances are a good way of helping students to maintain motivation and to accomplish their achievement. The final conclusion is addressed to the benefits of additional workshops employment in the course, which confirmhigherfinal scores-grades, achievement of creative results (facultative tasks) and confirmation of DG knowledge adaption

The benefits of an additional practice in descriptive geomerty course: non obligatory workshop at the Faculty of Civil Engineering in Belgrade

At the Faculty of Civil Engineering in Belgrade, in the Descriptive geometry (DG) course, non-obligatory workshops named “facultative task” are held for the three generations of freshman students with the aim to give students the opportunity to get higher final grade on the exam. The content of this workshop was a creative task, performed by a group of three students, offering free choice of a topic, i.e. the geometric structure associated with some real or imagery architectural/art-work object. After the workshops a questionnaire (composed by the professors at the course) is given to the students, in order to get their response on teaching/learning materials for the DG course and the workshop. During the workshop students performed one of the common tests for testing spatial abilities, named “paper folding". Based on the results of the questionnairethe investigation of the linkages between:students’ final achievements and spatial abilities, as well as students’ expectations of their performance on the exam, and how the students’ capacity to correctly estimate their grades were associated with expected and final grades, is provided. The goal was to give an evidence that a creative work, performed by a small group of students and self-assessment of their performances are a good way of helping students to maintain motivation and to accomplish their achievement. The final conclusion is addressed to the benefits of additional workshops employment in the course, which confirmhigherfinal scores-grades, achievement of creative results (facultative tasks) and confirmation of DG knowledge adaption

The contemporary visualization and modelling technologies and the techniques for the design of the green roofs

The contemporary design solutions are merging the boundaries between real and virtual world. The Landscape architecture like the other interdisciplinary field stepped in a contemporary technologies area focused on that, beside the good execution of works, designer solutions has to be more realistic and “touchable”. The opportunities provided by Virtual Reality are certainly not negligible, it is common knowledge that the designs in the world are already presented in this way so the Virtual Reality increasingly used. Following the example of the application of virtual reality in landscape architecture, this paper deals with proposals for the use of virtual reality in landscape architecture so that designers, clients and users would have a virtual sense of scope e.g. rooftop garden, urban areas, parks, roads, etc. It is a programming language that creates a series of images creating a whole, so certain parts can be controlled or even modified in VR. Virtual reality today requires a specific gadget, such as Occulus, HTC Vive, Samsung Gear VR and similar. The aim of this paper is to acquire new theoretical and practical knowledge in the interdisciplinary field of virtual reality, the ability to display using virtual reality methods, and to present through a brief overview the plant species used in the design and construction of an intensive roof garden in a Mediterranean climate, the basic characteristics of roofing gardens as well as the benefits they carry. Virtual and augmented reality as technology is a very powerful tool for landscape architects, when modeling roof gardens, parks, and urban areas. One of the most popular technologies used by landscape architects is Google Tilt Brush, which enables fast modeling. The Google Tilt Brush VR app allows modeling in three-dimensional virtual space using a palette to work with the use of a three dimensional brush. The terms of two "programmed" realities - virtual reality and augmented reality - are often confused. One thing they have in common, though, is VRML - Virtual Reality Modeling Language. In this paper are shown the ways on which this issue can be solved and by the way, get closer the term of Virtual Reality (VR), also all the opportunities which the Virtual reality offered us. As well, in this paper are shown the conditions of Mediterranean climate, the conceptual solution and the plant species which will be used by execution of intensive green roof on the motel “Marković”