Fully Automatic Segmentation of AP Pelvis X-rays via Random Forest Regression and Hierarchical Sparse Shape Composition

Knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic and robust approach for landmarking and segmentation of both pelvis and femur in a conventional AP X-ray. Our approach is based on random forest regression and hierarchical sparse shape composition. Experiments conducted on 436 clinical AP pelvis x-rays show that our approach achieves an average point-to-curve error around 1.3 mm for femur and 2.2 mm for pelvis, both with success rates around 98%. Compared to existing methods, our approach exhibits better performance in both the robustness and the accuracy.

Commentary: Dedication of Additional Resources to Evaluation and Low-Income Schools is Critical to Increasing Levels of Safe Walking and Bicycling to School

A commentary on Mendoza et al.'s article entitled, "Ethnic Minority Children’s Active Commuting to School and Association with Physical Activity and Pedestrian Safety Behaviors."

Automatic quantitation of multiple sclerosis lesions on MR images

A two-pronged approach for the automatic quantitation of multiple sclerosis (MS) lesions on magnetic resonance (MR) images has been developed. This method includes the design and use of a pulse sequence for improved lesion-to-tissue contrast (LTC) and seeks to identify and minimize the sources of false lesion classifications in segmented images. The new pulse sequence, referred to as AFFIRMATIVE (Attenuation of Fluid by Fast Inversion Recovery with MAgnetization Transfer Imaging with Variable Echoes), improves the LTC, relative to spin-echo images, by combining Fluid-Attenuated Inversion Recovery (FLAIR) and Magnetization Transfer Contrast (MTC). In addition to acquiring fast FLAIR/MTC images, the AFFIRMATIVE sequence simultaneously acquires fast spin-echo (FSE) images for spatial registration of images, which is necessary for accurate lesion quantitation. Flow has been found to be a primary source of false lesion classifications. Therefore, an imaging protocol and reconstruction methods are developed to generate "flow images" which depict both coherent (vascular) and incoherent (CSF) flow. An automatic technique is designed for the removal of extra-meningeal tissues, since these are known to be sources of false lesion classifications. A retrospective, three-dimensional (3D) registration algorithm is implemented to correct for patient movement which may have occurred between AFFIRMATIVE and flow imaging scans. Following application of these pre-processing steps, images are segmented into white matter, gray matter, cerebrospinal fluid, and MS lesions based on AFFIRMATIVE and flow images using an automatic algorithm. All algorithms are seamlessly integrated into a single MR image analysis software package. Lesion quantitation has been performed on images from 15 patient volunteers. The total processing time is less than two hours per patient on a SPARCstation 20. The automated nature of this approach should provide an objective means of monitoring the progression, stabilization, and/or regression of MS lesions in large-scale, multi-center clinical trials. ^

The Anomalous Merging of the African and North Atlantic Jet Streams during the Northern Hemisphere Winter of 2010

The North Atlantic jet stream during winter 2010 was unusually zonal, so the typically separated Atlantic and African jets were merged into one zonal jet. Moreover, the latitude–height structure and temporal variability of the North Atlantic jet during this winter were more characteristic of the North Pacific. This work examines the possibility of a flow regime change from an eddy-driven to a mixed eddy–thermally driven jet. A monthly jet zonality index is defined, which shows that a persistent merged jet state has occurred in the past, both at the end of the 1960s and during a few sporadic months. The anomalously zonal jet is found to be associated with anomalous tropical Pacific diabatic heating and eddy anomalies similar to those found during a negative North Atlantic Oscillation (NAO) state. A Lagrangian back-trajectory diagnosis of eight winters suggests the tropical Pacific is a source of momentum to the Atlantic and African jets and that this source was stronger during the winter of 2010. The results suggest that the combination of weak eddy variance and fluxes in the North Atlantic, along with strong tropical heating, act to push the jet toward a merged eddy–thermally driven state. The authors also find significant SST anomalies in the North Atlantic, which reinforce the anomalous zonal winds, particularly in the eastern Atlantic.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A novel Statistical Shape Model for treatment planning of Retinoblastoma

Purpose: Proper delineation of ocular anatomy in 3D imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic Resonance Imaging (MRI) is nowadays utilized in clinical practice for the diagnosis confirmation and treatment planning of retinoblastoma in infants, where it serves as a source of information, complementary to the Fundus or Ultrasound imaging. Here we present a framework to fully automatically segment the eye anatomy in the MRI based on 3D Active Shape Models (ASM), we validate the results and present a proof of concept to automatically segment pathological eyes. Material and Methods: Manual and automatic segmentation were performed on 24 images of healthy children eyes (3.29±2.15 years). Imaging was performed using a 3T MRI scanner. The ASM comprises the lens, the vitreous humor, the sclera and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens and the optic nerve, then aligning the model and fitting it to the patient. We validated our segmentation method using a leave-one-out cross validation. The segmentation results were evaluated by measuring the overlap using the Dice Similarity Coefficient (DSC) and the mean distance error. Results: We obtained a DSC of 94.90±2.12% for the sclera and the cornea, 94.72±1.89% for the vitreous humor and 85.16±4.91% for the lens. The mean distance error was 0.26±0.09mm. The entire process took 14s on average per eye. Conclusion: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor and the lens using MRI. We additionally present a proof of concept for fully automatically segmenting pathological eyes. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

Automatic estimation of noise parameters in Fourier-domain optical coherence tomography cross sectional images using statistical information

We present an application and sample independent method for the automatic discrimination of noise and signal in optical coherence tomography Bscans. The proposed algorithm models the observed noise probabilistically and allows for a dynamic determination of image noise parameters and the choice of appropriate image rendering parameters. This overcomes the observer variability and the need for a priori information about the content of sample images, both of which are challenging to estimate systematically with current systems. As such, our approach has the advantage of automatically determining crucial parameters for evaluating rendered image quality in a systematic and task independent way. We tested our algorithm on data from four different biological and nonbiological samples (index finger, lemon slices, sticky tape, and detector cards) acquired with three different experimental spectral domain optical coherence tomography (OCT) measurement systems including a swept source OCT. The results are compared to parameters determined manually by four experienced OCT users. Overall, our algorithm works reliably regardless of which system and sample are used and estimates noise parameters in all cases within the confidence interval of those found by observers.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

Fragmentation of Natural Resources Management: Experiences from Lake Kariba

This book is an output of the Defragmenting African Resources Management (DARMA) Project. Lake Kariba and its environs are a complex transboundary ecosystem with multiple, competing and often contested resource uses. The individual chapters in the book describe the current sectoral approach to natural resource management, the interconnections, and the need to adopt an ecosystem approach. The book is an essential reading for students, researchers, academics and managers in the environmental and natural resources sectors interested in advancing the ecosystems approach in management of commons in general and Southern Africa in particular. - See more at: http://www.plaas.org.za/plaas-publication/DARMA-Kariba-LV#sthash.7giSiWiB.dpuf

Desertification and Global Change: Innovative Management of Scarce Resources in Semi-Arid Areas. Experiences from development and research: Challenges for a better future

While most events related to the International Year of Deserts and Desertification 2006 took mainly a problem-oriented perspective and approach, the Bern Symposium held in May 2006 tried to adopt a more positive attitude by attempting to take stock of experience as well as best and worst practices in the past, both in development practice and in research. Through this deliberate focus on potentials, positive experiences, solutions and pathways, predominant passive and reactive attitudes and hopelessness might be better overcome. The Symposium was organized by CDE, NCCR North-South and Forum SLM.

Capitalisation of Experiences of the Swiss Support to Sustainable Management of Natural Resources (SMNR) in Bulgaria

Following the collapse of the communist regime in 1989, Bulgaria has undergone dramatic political, economic and social transformations. The transition process of the past two decades was characterized by several reforms to support democratisation of the political system and the functioning of a free-market economy. Since 1992, Switzerland has been active in Bulgaria providing assistance to the transition process, with support to Sustainable Management of Natural Resources (SMNR) starting in 1995. The SMNR Capitalisation of Experiences (CapEx) took place between March and September 2007, in the context of SDC phasing out its programmes in Bulgaria by the end of 2007 due to the country’s accession to the European Union. The CapEx exercise has culminated in the identification of 17 lessons learned. In the view of the CapEx team, many of these lessons are relevant for countries that are in the process of joining the EU, facing similar democratisation challenges as Bulgaria. Overall, the Swiss SMNR projects have been effective entry points to support areas that are crucial to democratic transitions, namely participation in public goods management, decentralisation, human capacity development in research and management, and preparation for EU membership. The specificity of the Swiss support stems from an approach that combines a long-term commitment with a clear thematic focus (forestry, biodiversity conservation and organic agriculture). The multistakeholder approach and diversification of support between local, regional and national levels are also important elements that contributed to make a difference in relation to other donors supporting the Bulgarian transition. At the institutional level, there are a number of challenges where the contribution of SMNR activities was only modest, namely improving the legal framework and creating more transparency and accountability, both of which are time and resource-consuming processes. In addition, the emergence of competent and sustainable non-government organisations (NGOs) is a complex process that requires support to membership based organisations, a challenge that was hardly met in the case of SMNR. Finally, reform of government institutions involved in management of natural resources is difficult to achieve via project support only, as it requires leverage and commitment at the level of policy dialogue. At the programme management level, the CapEx team notes that corruption was not systematically addressed in SMNR projects, indicating that more attention should be given to this issue at the outset of any new project.