188 research outputs found
The Medical Segmentation Decathlon
International challenges have become the de facto standard for comparative
assessment of image analysis algorithms given a specific task. Segmentation is
so far the most widely investigated medical image processing task, but the
various segmentation challenges have typically been organized in isolation,
such that algorithm development was driven by the need to tackle a single
specific clinical problem. We hypothesized that a method capable of performing
well on multiple tasks will generalize well to a previously unseen task and
potentially outperform a custom-designed solution. To investigate the
hypothesis, we organized the Medical Segmentation Decathlon (MSD) - a
biomedical image analysis challenge, in which algorithms compete in a multitude
of both tasks and modalities. The underlying data set was designed to explore
the axis of difficulties typically encountered when dealing with medical
images, such as small data sets, unbalanced labels, multi-site data and small
objects. The MSD challenge confirmed that algorithms with a consistent good
performance on a set of tasks preserved their good average performance on a
different set of previously unseen tasks. Moreover, by monitoring the MSD
winner for two years, we found that this algorithm continued generalizing well
to a wide range of other clinical problems, further confirming our hypothesis.
Three main conclusions can be drawn from this study: (1) state-of-the-art image
segmentation algorithms are mature, accurate, and generalize well when
retrained on unseen tasks; (2) consistent algorithmic performance across
multiple tasks is a strong surrogate of algorithmic generalizability; (3) the
training of accurate AI segmentation models is now commoditized to non AI
experts
Risk accelerators in disasters : insights from the typhoon Haiyan response on humanitarian information management and decision support
Published version of a chapter in the book: Advanced Information Systems Engineering. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-319-07881-6_2Modern societies are increasingly threatened by disasters that require rapid response through ad-hoc collaboration among a variety of actors and organizations. The complexity within and across today's societal, economic and environmental systems defies accurate predictions and assessments of damages, humanitarian needs, and the impact of aid. Yet, decision-makers need to plan, manage and execute aid response under conditions of high uncertainty while being prepared for further disruptions and failures. This paper argues that these challenges require a paradigm shift: instead of seeking optimality and full efficiency of procedures and plans, strategies should be developed that enable an acceptable level of aid under all foreseeable eventualities. We propose a decision- and goal-oriented approach that uses scenarios to systematically explore future developments that may have a major impact on the outcome of a decision. We discuss to what extent this approach supports robust decision-making, particularly if time is short and the availability of experts is limited. We interlace our theoretical findings with insights from experienced humanitarian decision makers we interviewed during a field research trip to the Philippines in the aftermath of Typhoon Haiyan
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Vegetational Evaluation of Pinyon-Juniper Cabling in South-Central New Mexico
Vegetational comparisons were made between areas where pinyon-juniper vegetation had been cabled in 1954 and uncabled areas. Total tree density on the cabled areas was about 80% of that on control areas. Basal area and canopy cover of trees was substantially lower on control areas than on cabled areas. Rhus trilobata and Xanthocephalum sarothrae apparently were the only shrubby species that responded to the cabling treatment. Basal cover of Bouteloua gracilis, Eragrostis erosa, and Muhlenbergia pauciflora was significantly greater on the control areas than on the cabled area.This material was digitized as part of a cooperative project between the Society for Range Management and the University of Arizona Libraries.The Journal of Range Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform August 202
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