43,201 research outputs found
Digital Image Access & Retrieval
The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio
Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates
The study of cerebral anatomy in developing neonates is of great importance for
the understanding of brain development during the early period of life. This
dissertation therefore focuses on three challenges in the modelling of cerebral
anatomy in neonates during brain development. The methods that have been
developed all use Magnetic Resonance Images (MRI) as source data.
To facilitate study of vascular development in the neonatal period, a set of image
analysis algorithms are developed to automatically extract and model cerebral
vessel trees. The whole process consists of cerebral vessel tracking from
automatically placed seed points, vessel tree generation, and vasculature
registration and matching. These algorithms have been tested on clinical Time-of-
Flight (TOF) MR angiographic datasets.
To facilitate study of the neonatal cortex a complete cerebral cortex segmentation
and reconstruction pipeline has been developed. Segmentation of the neonatal
cortex is not effectively done by existing algorithms designed for the adult brain
because the contrast between grey and white matter is reversed. This causes pixels
containing tissue mixtures to be incorrectly labelled by conventional methods. The
neonatal cortical segmentation method that has been developed is based on a novel
expectation-maximization (EM) method with explicit correction for mislabelled
partial volume voxels. Based on the resulting cortical segmentation, an implicit
surface evolution technique is adopted for the reconstruction of the cortex in
neonates. The performance of the method is investigated by performing a detailed
landmark study.
To facilitate study of cortical development, a cortical surface registration algorithm
for aligning the cortical surface is developed. The method first inflates extracted
cortical surfaces and then performs a non-rigid surface registration using free-form
deformations (FFDs) to remove residual alignment. Validation experiments using
data labelled by an expert observer demonstrate that the method can capture local
changes and follow the growth of specific sulcus
High-Throughput System for the Early Quantification of Major Architectural Traits in Olive Breeding Trials Using UAV Images and OBIA Techniques
The need for the olive farm modernization have encouraged the research of more efficient crop management strategies through cross-breeding programs to release new olive cultivars more suitable for mechanization and use in intensive orchards, with high quality production and resistance to biotic and abiotic stresses. The advancement of breeding programs are hampered by the lack of efficient phenotyping methods to quickly and accurately acquire crop traits such as morphological attributes (tree vigor and vegetative growth habits), which are key to identify desirable genotypes as early as possible. In this context, an UAV-based high-throughput system for olive breeding program applications was developed to extract tree traits in large-scale phenotyping studies under field conditions. The system consisted of UAV-flight configurations, in terms of flight altitude and image overlaps, and a novel, automatic, and accurate object-based image analysis (OBIA) algorithm based on point clouds, which was evaluated in two experimental trials in the framework of a table olive breeding program, with the aim to determine the earliest date for suitable quantifying of tree architectural traits. Two training systems (intensive and hedgerow) were evaluated at two very early stages of tree growth: 15 and 27 months after planting. Digital Terrain Models (DTMs) were automatically and accurately generated by the algorithm as well as every olive tree identified, independently of the training system and tree age. The architectural traits, specially tree height and crown area, were estimated with high accuracy in the second flight campaign, i.e. 27 months after planting. Differences in the quality of 3D crown reconstruction were found for the growth patterns derived from each training system. These key phenotyping traits could be used in several olive breeding programs, as well as to address some agronomical goals. In addition, this system is cost and time optimized, so that requested architectural traits could be provided in the same day as UAV flights. This high-throughput system may solve the actual bottleneck of plant phenotyping of "linking genotype and phenotype," considered a major challenge for crop research in the 21st century, and bring forward the crucial time of decision making for breeders
Clustering with shallow trees
We propose a new method for hierarchical clustering based on the optimisation
of a cost function over trees of limited depth, and we derive a
message--passing method that allows to solve it efficiently. The method and
algorithm can be interpreted as a natural interpolation between two well-known
approaches, namely single linkage and the recently presented Affinity
Propagation. We analyze with this general scheme three biological/medical
structured datasets (human population based on genetic information, proteins
based on sequences and verbal autopsies) and show that the interpolation
technique provides new insight.Comment: 11 pages, 7 figure
Beta Thalassemia Carriers detection empowered federated Learning
Thalassemia is a group of inherited blood disorders that happen when
hemoglobin, the protein in red blood cells that carries oxygen, is not made
enough. It is found all over the body and is needed for survival. If both
parents have thalassemia, a child's chance of getting it increases. Genetic
counselling and early diagnosis are essential for treating thalassemia and
stopping it from being passed on to future generations. It may be hard for
healthcare professionals to differentiate between people with thalassemia
carriers and those without. The current blood tests for beta thalassemia
carriers are too expensive, take too long, and require too much screening
equipment. The World Health Organization says there is a high death rate for
people with thalassemia. Therefore, it is essential to find thalassemia
carriers to act quickly. High-performance liquid chromatography (HPLC), the
standard test method, has problems such as cost, time, and equipment needs. So,
there must be a quick and cheap way to find people carrying the thalassemia
gene. Using federated learning (FL) techniques, this study shows a new way to
find people with the beta-thalassemia gene. FL allows data to be collected and
processed on-site while following privacy rules, making it an excellent choice
for sensitive health data. Researchers used FL to train a model for
beta-thalassemia carriers by looking at the complete blood count results and
red blood cell indices. The model was 92.38 % accurate at telling the
difference between beta-thalassemia carriers and people who did not have the
disease. The proposed FL model is better than other published methods in terms
of how well it works, how reliable it is, and how private it is. This research
shows a promising, quick, accurate, and low-cost way to find thalassemia
carriers and opens the door for screening them on a large scale.Comment: pages 17, figures
Simple identification tools in FishBase
Simple identification tools for fish species were included in the FishBase information system from its inception. Early tools made use of the relational model and characters like fin ray meristics. Soon pictures and drawings were added as a further help, similar to a field guide. Later came the computerization of existing dichotomous keys, again in combination with pictures and other information, and the ability to restrict possible species by country, area, or taxonomic group. Today, www.FishBase.org offers four different ways to identify species. This paper describes these tools with their advantages and disadvantages, and suggests various options for further
development. It explores the possibility of a holistic and integrated computeraided strategy
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