Results 141 to 150 of about 496,156 (331)

Automatic Image Annotation through Multi-Topic Text Categorization [PDF]

, 2006
Sheng Gao, Dehong Wang, Chin‐Hui Lee
openalex   +1 more source

NanoCMSer: a consensus molecular subtype stratification tool for fresh‐frozen and paraffin‐embedded colorectal cancer samples

Molecular Oncology, EarlyView.
Consensus molecular subtypes (CMS1‐4) have been identified to study colorectal cancer heterogeneity and serve as potential biomarkers. In this study, we developed and evaluated NanoCMSer, a NanoString‐based classifier using 55 genes, optimized for FF and FFPE to facilitate the clinical evaluation of CMS subtyping.
Arezo Torang, Simone van de Weerd, Veerle Lammers, Sander van Hooff, Inge van den Berg, Saskia van den Bergh, Miriam Koopman, Jan N. IJzermans, Jeanine M. L. Roodhart, Jan Koster, Jan Paul Medema   +10 more
wiley   +1 more source

Evaluating the use of Instagram images color histograms and hashtags sets for automatic image annotation. [PDF]

Front Big Data, 2023
Giannoulakis S, Tsapatsoulis N, Djouvas C.   +2 more
europepmc   +1 more source

Can Global Visual Features Improve Tag Recommendation for Image Annotation?

Future Internet, 2010
Recent advances in the fields of digital photography, networking and computing, have made it easier than ever for users to store and share photographs.
Oge Marques, Arthur Pitman, Mathias Lux
doaj   +1 more source

Automatic Semantic Annotation of Images using Spatial Hidden Markov Model [PDF]

, 2006
Feiyang Yu, Horace H. S. Ip
openalex   +1 more source

Obesity alters the fitness of peritumoral adipose tissue, exacerbating tumor invasiveness in renal cancer through the induction of ADAM12 and CYP1B1

Molecular Oncology, EarlyView.
Tumor microenvironment drives cancer formation and progression. We analyzed the role of human cancer‐associated adipocytes from patients with renal cell carcinoma (RCC) stratified as lean, overweight, or obese. RNA‐seq demonstrated that, among the most altered genes involved in the tumor–stroma crosstalk, are ADAM12 and CYP1B1, which were proven to be ...
Sepehr Torabinejad, Caterina Miro, Annarita Nappi, Francesco Del Giudice, Annunziata Gaetana Cicatiello, Serena Sagliocchi, Lucia Acampora, Federica Restolfer, Melania Murolo, Emery Di Cicco, Federico Capone, Ciro Imbimbo, Monica Dentice, Felice Crocetto   +13 more
wiley   +1 more source

Visual Image Annotation for Bowel Obstruction: Repeatability and Agreement with Manual Annotation and Neural Networks. [PDF]

J Digit Imaging, 2023
Murphy PM.
europepmc   +1 more source

Manual Annotation and Automatic Image Processing of Multimodal Emotional Behaviors in TV Interviews [PDF]

, 2006
Jean‐Claude Martin, George Caridakis, Laurence Devillers, Kostas Karpouzis, Sarkis Abrilian   +4 more
openalex   +1 more source

Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon

Molecular Oncology, EarlyView.
Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran, Clarence Yapp, Gregory J. Baker, Johanna Beyer, Young Hwan Chang, Allison L. Creason, Robert Krueger, Jeremy Muhlich, Nathan Heath Patterson, Kevin Sidak, Damir Sudar, Adam J. Taylor, Luke Ternes, Jakob Troidl, Xie Yubin, Artem Sokolov, Darren R. Tyson   +16 more
wiley   +1 more source

Extending UML for Conceptual Modeling of Annotation of Medical Images [PDF]

arXiv, 2013
Imaging has occupied a huge role in the management of patients, whether hospitalized or not. Depending on the patients clinical problem, a variety of imaging modalities were available for use. This gave birth of the annotation of medical image process. The annotation is intended to image analysis and solve the problem of semantic gap.
arxiv