FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3048892387> ?p ?o ?g. }

• W3048892387 abstract "Abstract Image texture, the relative spatial arrangement of intensity values in an image, encodes valuable information about the scene. As it stands, much of this potential information remains untapped. Understanding how to decipher textural details would afford another method of extracting knowledge of the physical world from images. In this work, we attempt to bridge the gap in research between quantitative texture analysis and the visual perception of textures. The impact of changes in image texture on human observer’s ability to perform signal detection and localization tasks in complex digital images is not understood. We examine this critical question by studying task-based human observer performance in detecting and localizing signals in tomographic breast images. We have also investigated how these changes impact the formation of second-order image texture. We used digital breast tomosynthesis (DBT) an FDA approved tomographic X-ray breast imaging method as the modality of choice to show our preliminary results. Our human observer studies involve localization ROC (LROC) studies for low contrast mass detection in DBT. Simulated images are used as they offer the benefit of known ground truth. Our results prove that changes in system geometry or processing leads to changes in image texture magnitudes. We show that the variations in several well-known texture features estimated in digital images correlate with human observer detection–localization performance for signals embedded in them. This insight can allow efficient and practical techniques to identify the best imaging system design and algorithms or filtering tools by examining the changes in these texture features. This concept linking texture feature estimates and task based image quality assessment can be extended to several other imaging modalities and applications as well. It can also offer feedback in system and algorithm designs with a goal to improve perceptual benefits. Broader impact can be in wide array of areas including imaging system design, image processing, data science, machine learning, computer vision, perceptual and vision science. Our results also point to the caution that must be exercised in using these texture features as image-based radiomic features or as predictive markers for risk assessment as they are sensitive to system or image processing changes." @default.
• W3048892387 created "2020-08-18" @default.
• W3048892387 creator A5057032078 @default.
• W3048892387 creator A5061814059 @default.
• W3048892387 creator A5084783173 @default.
• W3048892387 date "2020-08-11" @default.
• W3048892387 modified "2023-10-17" @default.
• W3048892387 title "On the correlation between second order texture features and human observer detection performance in digital images" @default.
• W3048892387 cites W1492054812 @default.
• W3048892387 cites W1550497686 @default.
• W3048892387 cites W1552795132 @default.
• W3048892387 cites W1967426304 @default.
• W3048892387 cites W1980429329 @default.
• W3048892387 cites W1989438286 @default.
• W3048892387 cites W1989763850 @default.
• W3048892387 cites W1991996248 @default.
• W3048892387 cites W2003304826 @default.
• W3048892387 cites W2003894496 @default.
• W3048892387 cites W2018545844 @default.
• W3048892387 cites W2019090719 @default.
• W3048892387 cites W2021940526 @default.
• W3048892387 cites W2025539136 @default.
• W3048892387 cites W2032138177 @default.
• W3048892387 cites W2032533296 @default.
• W3048892387 cites W2032852933 @default.
• W3048892387 cites W2040825244 @default.
• W3048892387 cites W2044465660 @default.
• W3048892387 cites W2045791751 @default.
• W3048892387 cites W2053883262 @default.
• W3048892387 cites W2055483062 @default.
• W3048892387 cites W2059432853 @default.
• W3048892387 cites W2065686377 @default.
• W3048892387 cites W2074216275 @default.
• W3048892387 cites W2103004421 @default.
• W3048892387 cites W2116775109 @default.
• W3048892387 cites W2117395697 @default.
• W3048892387 cites W2125027853 @default.
• W3048892387 cites W2126159379 @default.
• W3048892387 cites W2128561383 @default.
• W3048892387 cites W2146986429 @default.
• W3048892387 cites W2153777140 @default.
• W3048892387 cites W2158564760 @default.
• W3048892387 cites W2161190560 @default.
• W3048892387 cites W2290987211 @default.
• W3048892387 cites W2327203407 @default.
• W3048892387 cites W2592421164 @default.
• W3048892387 cites W2594144374 @default.
• W3048892387 cites W2600642189 @default.
• W3048892387 cites W2606926876 @default.
• W3048892387 cites W2611468129 @default.
• W3048892387 cites W2763355946 @default.
• W3048892387 cites W2790642312 @default.
• W3048892387 cites W2791611005 @default.
• W3048892387 cites W2895238724 @default.
• W3048892387 cites W2990603864 @default.
• W3048892387 cites W3023914373 @default.
• W3048892387 doi "https://doi.org/10.1038/s41598-020-69816-z" @default.
• W3048892387 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7419558" @default.
• W3048892387 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32782415" @default.
• W3048892387 hasPublicationYear "2020" @default.
• W3048892387 type Work @default.
• W3048892387 sameAs 3048892387 @default.
• W3048892387 citedByCount "4" @default.
• W3048892387 countsByYear W30488923872022 @default.
• W3048892387 countsByYear W30488923872023 @default.
• W3048892387 crossrefType "journal-article" @default.
• W3048892387 hasAuthorship W3048892387A5057032078 @default.
• W3048892387 hasAuthorship W3048892387A5061814059 @default.
• W3048892387 hasAuthorship W3048892387A5084783173 @default.
• W3048892387 hasBestOaLocation W30488923871 @default.
• W3048892387 hasConcept C115961682 @default.
• W3048892387 hasConcept C121332964 @default.
• W3048892387 hasConcept C121608353 @default.
• W3048892387 hasConcept C126322002 @default.
• W3048892387 hasConcept C146849305 @default.
• W3048892387 hasConcept C153180895 @default.
• W3048892387 hasConcept C154945302 @default.
• W3048892387 hasConcept C2776502983 @default.
• W3048892387 hasConcept C2780472235 @default.
• W3048892387 hasConcept C2780704645 @default.
• W3048892387 hasConcept C2781195486 @default.
• W3048892387 hasConcept C2781281974 @default.
• W3048892387 hasConcept C31972630 @default.
• W3048892387 hasConcept C41008148 @default.
• W3048892387 hasConcept C42781572 @default.
• W3048892387 hasConcept C530470458 @default.
• W3048892387 hasConcept C62520636 @default.
• W3048892387 hasConcept C63099799 @default.
• W3048892387 hasConcept C71924100 @default.
• W3048892387 hasConcept C9417928 @default.
• W3048892387 hasConceptScore W3048892387C115961682 @default.
• W3048892387 hasConceptScore W3048892387C121332964 @default.
• W3048892387 hasConceptScore W3048892387C121608353 @default.
• W3048892387 hasConceptScore W3048892387C126322002 @default.
• W3048892387 hasConceptScore W3048892387C146849305 @default.
• W3048892387 hasConceptScore W3048892387C153180895 @default.
• W3048892387 hasConceptScore W3048892387C154945302 @default.
• W3048892387 hasConceptScore W3048892387C2776502983 @default.
• W3048892387 hasConceptScore W3048892387C2780472235 @default.
• W3048892387 hasConceptScore W3048892387C2780704645 @default.

• next