Structural asessment and strengthening of Atatürk's mausoleum, Anitkabir

Anıtkabir is the mausoleum of Mustafa Kemal Atatürk, the commander of Turkish War of Independence and the founder of Republic of Turkey. Rather than a work of architecture, Anıtkabir has been a symbol and a focal center of Atatürk’s principles, republican revolutions and modern Turkey

Binary and nonbinary description of hypointensity for search and retrieval of brain MR images

Diagnosis accuracy in the medical field, is mainly affected by either lack of sufficient understanding of some diseases or the inter/intra-observer variability of the diagnoses. We believe that mining of large medical databases can help improve the current status of disease understanding and decision making. In a previous study based on binary description of hypointensity in the brain, it was shown that brain iron accumulation shape provides additional information to the shape-insensitive features, such as the total brain iron load, that are commonly used in clinics. This paper proposes a novel, nonbinary description of hypointensity in the brain based on principal component analysis. We compare the complementary and redundant information provided by the two descriptions using Kendall's rank correlation coefficient in order to better understand the individual descriptions of iron accumulation in the brain and obtain a more robust and accurate search and retrieval system

Biomedical image time series registration with particle filtering (Parçacık süzgeci ile biyomedikal görüntü zaman serisi çakıştırma)

We propose a family of methods for biomedical image time series registration based on Particle filtering. The first method applies an intensity-based information-theoretic approach to calculate importance weights. An effective second group of methods use landmark-based approaches for the same purpose by automatically detecting intensity maxima or SIFT interest points from image time series. A brute-force search for the best alignment usually produces good results with proper cost functions, but becomes computationally expensive if the whole search space is explored. Hill climbing optimizations seek local optima. Particle filtering avoids local solutions by introducing randomness and sequentially updating the posterior distribution representing probable solutions. Thus, it can be more robust for the registration of image time series. We show promising preliminary results on dendrite image time series

Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study

The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography (CT) scans. Vessel segmentation is fundamental in computer aided processing of data generated by 3D imaging modalities. As manual vessel segmentation is prohibitively time consuming, any real world application requires some form of automation. Several approaches exist for automated vessel segmentation, but judging their relative merits is difficult due to a lack of standardized evaluation. We present an annotated reference dataset containing 20 CT scans and propose nine categories to perform a comprehensive evaluation of vessel segmentation algorithms from both academia and industry. Twenty algorithms participated in the VESSEL12 challenge, held at International Symposium on Biomedical Imaging (ISBI) 2012. All results have been published at the VESSEL12 website http://vessel12.grand-challenge.org. The challenge remains ongoing and open to new participants. Our three contributions are: (1) an annotated reference dataset available online for evaluation of new algorithms; (2) a quantitative scoring system for objective comparison of algorithms; and (3) performance analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases.Rudyanto, RD.; Kerkstra, S.; Van Rikxoort, EM.; Fetita, C.; Brillet, P.; Lefevre, C.; Xue, W.... (2014). Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study. Medical Image Analysis. 18(7):1217-1232. doi:10.1016/j.media.2014.07.003S1217123218

Imaging of subsurface lineaments in the southwestern part of the Thrace Basin from gravity data

Linear anomalies, as an indicator of the structural features of some geological bodies, are very important for the interpretation of gravity and magnetic data. In this study, an image processing technique known as the Hough transform (HT) algorithm is described for determining invisible boundaries and extensions in gravity anomaly maps. The Hough function implements the Hough transform used to extract straight lines or circles within two-dimensional potential field images. It is defined as image and Hough space. In the Hough domain, this function transforms each nonzero point in the parameter domain to a sinusoid. In the image space, each point in the Hough space is transformed to a straight line or circle. Lineaments are depicted from these straight lines which are transformed in the image domain. An application of the Hough transform to the Bouguer anomaly map of the southwestern part of the Thrace Basin, NW Turkey, shows the effectiveness of the proposed approach. Based on geological data and gravity data, the structural features in the southwestern part of the Thrace Basin are investigated by applying the proposed approach and the Blakely and Simpson method. Lineaments identified by these approaches are generally in good accordance with previously-mapped surface faults

BIAFLOWS: A Collaborative Framework to Reproducibly Deploy and Benchmark Bioimage Analysis Workflows

Peer reviewe

SSNOMBACTER: A collection of scattering-type scanning near-field optical microscopy and atomic force microscopy images of bacterial cells

In recent years, a variety of imaging techniques operating at nanoscale resolution have been reported. These techniques have the potential to enrich our understanding of bacterial species relevant to human health, such as antibiotic-resistant pathogens. However, owing to the novelty of these techniques, their use is still confined to addressing very particular applications, and their availability is limited owing to associated costs and required expertise. Among these, scattering-type scanning near field optical microscopy (s-SNOM) has been demonstrated as a powerful tool for exploring important optical properties at nanoscale resolution, depending only on the size of a sharp tip. Despite its huge potential to resolve aspects that cannot be tackled otherwise, the penetration of s-SNOM into the life sciences is still proceeding at a slow pace for the aforementioned reasons