Results 101 to 110 of about 496,156 (331)
FEBS Letters, EarlyView.The enzyme 5‐lipoxygenase (5‐LOX) catalyzes the first step in the biosynthesis of leukotrienes (LTs) involved in inflammatory pathophysiology. After cellular stimulation, 5‐LOX translocates to the nucleus, interacting with the 5‐LOX‐activating protein (FLAP) to form LTA4 from arachidonic acid (AA).
Erik Romp +5 more
wiley +1 more source
Analysing Word Importance for Image Annotation [PDF]
arXiv, 2013 Image annotation provides several keywords automatically for a given image based on various tags to describe its contents which is useful in Image retrieval. Various researchers are working on text based and content based image annotations [7,9]. It is seen, in traditional Image annotation approaches, annotation words are treated equally without ...
arxiv
Enrichment of the NLST and NSCLC-Radiomics computed tomography collections with AI-derived annotations [PDF]
arXiv, 2023 Public imaging datasets are critical for the development and evaluation of automated tools in cancer imaging. Unfortunately, many do not include annotations or image-derived features, complicating their downstream analysis. Artificial intelligence-based annotation tools have been shown to achieve acceptable performance and thus can be used to ...
arxiv
XML-Based Image Annotation: PAIS - a Personal Annotated Image Server [PDF]
, 2000 (no ...
Brinkley, James F, Lober, W. B.
core +1 more source
An EEG-Based Image Annotation System [PDF]
, 2018 The success of deep learning in computer vision has greatly increased the need for annotated image datasets. We propose an EEG (Electroencephalogram)-based image annotation system. While humans can recognize objects in 20-200 milliseconds, the need to manually label images results in a low annotation throughput.
Viral Parekh +3 more
openaire +2 more sources
Leveraging the crowd for annotation of retinal images [PDF]
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015 Medical data presents a number of challenges. It tends to be unstructured, noisy and protected. To train algorithms to understand medical images, doctors can label the condition associated with a particular image, but obtaining enough labels can be difficult.
Leifman, George +3 more
openaire +4 more sources
Subpar reporting of pre‐analytical variables in RNA‐focused blood plasma studies
Molecular Oncology, EarlyView.Pre‐analytical variables strongly influence the analysis of extracellular RNA (cell‐free RNA; exRNA) derived from blood plasma. Their reporting is essential to allow interpretation and replication of results. By evaluating 200 exRNA studies, we pinpoint a lack of reporting pre‐analytical variables associated with blood collection, plasma preparation ...
Céleste Van Der Schueren +16 more
wiley +1 more source
From Content-Based Image Retrieval by Shape to Image Annotation
Advances in Electrical and Computer Engineering, 2010 In many areas such as commerce, medical investigations, and others, large collections of digital images are being created. Search operations inside these collections of images are usually based on low-level features of objects contained in an image ...
MOCANU, I.
doaj +1 more source
Cograph Regularized Collective Nonnegative Matrix Factorization for Multilabel Image Annotation
IEEE Access, 2019 Automatic image annotation is an effective and straightforward way to facilitate many applications in computer vision. However, manually annotating images is a computation-expensive and labor-intensive task. To address these problems, this paper proposes
Juli Zhang +3 more
doaj +1 more source
Using Hausdorff Distance for New Medical Image Annotation [PDF]
arXiv, 2012 Medical images annotation is most of the time a repetitive hard task. Collecting old similar annotations and assigning them to new medical images may not only enhance the annotation process, but also reduce ambiguity caused by repetitive annotations. The goal of this work is to propose an approach based on Hausdorff distance able to compute similarity ...
arxiv