Computer-assisted detection of lung cancer nudules in medical chest X-rays

Diagnostic medicine was revolutionized in 1895 with Rontgen's discovery of x-rays. X-ray photography has played a very prominent role in diagnostics of all kinds since then and continues to do so. It is true that more sophisticated and successful medical imaging systems are available. These include Magnetic Resonance Imaging (MRI), Computerized Tomography (CT) and Positron Emission Tomography (PET). However, the hardware instalment and operation costs of these systems remain considerably higher than x-ray systems. Conventional x-ray photography also has the advantage of producing an image in significantly less time than MRI, CT and PET. X-ray photography is still used extensively, especially in third world countries. The routine diagnostic tool for chest complaints is the x-ray. Lung cancer may be diagnosed by the identification of a lung cancer nodule in a chest x-ray. The cure of lung cancer depends upon detection and diagnosis at an early stage. Presently the five-year survival rate of lung cancer patients is approximately 10%. If lung cancer can be detected when the tumour is still small and localized, the five-year survival rate increases to about 40%. However, currently only 20% of lung cancer cases are diagnosed at this early stage. Giger et al wrote that "detection and diagnosis of cancerous lung nodules in chest radiographs are among the most important and difficult tasks performed by radiologists"

Image Feature Information Extraction for Interest Point Detection: A Comprehensive Review

Interest point detection is one of the most fundamental and critical problems in computer vision and image processing. In this paper, we carry out a comprehensive review on image feature information (IFI) extraction techniques for interest point detection. To systematically introduce how the existing interest point detection methods extract IFI from an input image, we propose a taxonomy of the IFI extraction techniques for interest point detection. According to this taxonomy, we discuss different types of IFI extraction techniques for interest point detection. Furthermore, we identify the main unresolved issues related to the existing IFI extraction techniques for interest point detection and any interest point detection methods that have not been discussed before. The existing popular datasets and evaluation standards are provided and the performances for eighteen state-of-the-art approaches are evaluated and discussed. Moreover, future research directions on IFI extraction techniques for interest point detection are elaborated

Exploiting Spatio-Temporal Coherence for Video Object Detection in Robotics

This paper proposes a method to enhance video object detection for indoor environments in robotics. Concretely, it exploits knowledge about the camera motion between frames to propagate previously detected objects to successive frames. The proposal is rooted in the concepts of planar homography to propose regions of interest where to find objects, and recursive Bayesian filtering to integrate observations over time. The proposal is evaluated on six virtual, indoor environments, accounting for the detection of nine object classes over a total of ∼ 7k frames. Results show that our proposal improves the recall and the F1-score by a factor of 1.41 and 1.27, respectively, as well as it achieves a significant reduction of the object categorization entropy (58.8%) when compared to a two-stage video object detection method used as baseline, at the cost of small time overheads (120 ms) and precision loss (0.92).</p

A pilot study on discriminative power of features of superficial venous pattern in the hand

The goal of the project is to develop an automatic way to identify, represent the superficial vasculature of the back hand and investigate its discriminative power as biometric feature. A prototype of a system that extracts the superficial venous pattern of infrared images of back hands will be described. Enhancement algorithms are used to solve the lack of contrast of the infrared images. To trace the veins, a vessel tracking technique is applied, obtaining binary masks of the superficial venous tree. Successively, a method to estimate the blood vessels calibre, length, the location and angles of vessel junctions, will be presented. The discriminative power of these features will be studied, independently and simultaneously, considering two features vector. Pattern matching of two vasculature maps will be performed, to investigate the uniqueness of the vessel network / L’obiettivo del progetto è di sviluppare un metodo automatico per identificare e rappresentare la rete vascolare superficiale presente nel dorso della mano ed investigare sul suo potere discriminativo come caratteristica biometrica. Un prototipo di sistema che estrae l’albero superficiale delle vene da immagini infrarosse del dorso della mano sarà descritto. Algoritmi per il miglioramento del contrasto delle immagini infrarosse saranno applicati. Per tracciare le vene, una tecnica di tracking verrà utilizzata per ottenere una maschera binaria della rete vascolare. Successivamente, un metodo per stimare il calibro e la lunghezza dei vasi sanguigni, la posizione e gli angoli delle giunzioni sarà trattato. Il potere discriminativo delle precedenti caratteristiche verrà studiato ed una tecnica di pattern matching di due modelli vascolari sarà presentata per verificare l’unicità di quest

PRODUCTION, EXCHANGE AND SOCIAL INTERACTION IN THE GREEN RIVER REGION OF WESTERN KENTUCKY: A MULTISCALAR APPROACH TO THE ANALYSIS OF TWO SHELL MIDDEN SITES

The Green River region of western Kentucky has been a focus of Archaic period research since 1915. Currently, the region is playing an important role in discussions of Archaic hunter-gatherer cultural complexity. Unfortunately, many of the larger Green River sites contain several archaeological components ranging from the Early to Late Archaic periods. Understanding culture change requires that these multiple components somehow be sorted and addressed individually. Detailed re-analyses of Works Progress Administration (WPA) era artifact collections from two archaeological sites in the Green River region – the Baker (15Mu12) and Chiggerville (15Oh1) shell middens – indicate that these sites are relatively isolated Middle and Late Archaic components, respectively. The relatively unmixed character of Baker and Chiggerville makes these sites excellent candidates for evaluating aspects of complexity during the Archaic. After developing a theoretical basis for evaluating the relative complexity of the social organization of the Baker and Chiggerville site inhabitants on the basis of the material record they left behind, I employ detailed analyses of the bone, antler, and stone tools from these two sites to examine six microscalar aspects of complexity – technological organization, subsistence, specialization, leadership, communication networks, and exchange. These microscalar aspects of complexity all can be linked materially to the archaeological record of the Green River region and can be evaluated as proxies for changes in social organization among the hunter-gatherers who inhabited this region during the Middle and Late Archaic periods. Although the Baker assemblage indicated greater complexity in communication networks and certain proxies for leadership and technological organization, most indicators suggest that the Chiggerville site inhabitants were the more complexly organized group and were in the process of developing a tribal-like social formation. This research, therefore, tentatively supports the hypothesis of increasing complexity through time during the Archaic. However, marked differences in the technological strategies utilized by the Baker and Chiggerville site inhabitants indicates these groups may not have been historically related, thereby violating one of the primary assumptions of the project. If this alternative hypothesis is confirmed through additional research, then no conclusions concerning change through time can be derived from this study