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Image metadata reasoning for improved clinical decision support

Sonja Zillner, Daniel Sonntag
2012 Network Modeling Analysis in Health Informatics and Bioinformatics  
Today, clinicians rely more and more on medical images for screening, diagnosis, treatment planning, and follow-up examinations.  ...  While medical images provide a wealth of information for clinicians, content information cannot be automatically integrated into advanced medical applications such as those for the clinical decision support  ...  The responsibility for this publication lies with the authors.  ... 
doi:10.1007/s13721-012-0003-9 dblp:journals/netmahib/ZillnerS12 fatcat:4w4h36vgozfdpcpx3yu3phmpk4

Reasoning-Based Patient Classification for Enhanced Medical Image Annotation [chapter]

Sonja Zillner
2010 Lecture Notes in Computer Science  
Although, there exist several approaches for semantic image annotation, those approaches do not make use of practical clinical knowledge, such as best practice solutions or clinical guidelines.  ...  But still a generic and flexible image understanding is missing.  ...  The responsibility for this publication lies with the author. We are also thankful to Kamal Najib for his support with implementation tasks.  ... 
doi:10.1007/978-3-642-13486-9_17 fatcat:j27bobkf3bet7kt4ypaesi435i

Digital pen in mammography patient forms

Daniel Sonntag, Marcus Liwicki, Markus Weber
2011 Proceedings of the 13th international conference on multimodal interfaces - ICMI '11  
The resulting, automatically generated PDF report is then stored in a semantic backend system for further use and contains all transcribed annotations as well as all recognised sketches.  ...  In order to improve reporting practices im mammography, we allow the radiologist to write structured reports with a special pen on normal paper.  ...  ACKNOWLEDGEMENTS This research has been supported in part by the THESEUS Program in the MEDICO Project, which is funded by the German Federal Ministry of Economics and Technology under the grant number  ... 
doi:10.1145/2070481.2070537 dblp:conf/icmi/SonntagLW11 fatcat:iwffzllagjbgpi2ihbxp7xkige

Design and Implementation of a Semantic Dialogue System for Radiologists [article]

Daniel Sonntag and Martin Huber and Manuel Möller and Alassane Ndiaye and Sonja Zillner and Alexander Cavallaro
2017 arXiv   pre-print
Ontology modeling provides the backbone for knowledge representation in the dialogue shell and the specific medical application domain; ontology structures are the communication basis of our combined semantic  ...  MEDICO addresses the need for advanced semantic technologies in the search for medical image and patient data.  ...  We would like to thank Matthieu Deru for the implementation of the semantic interface elements.  ... 
arXiv:1701.07381v1 fatcat:f6ywhufuc5hnjlruhilzyeqh6a

Interleaved Text/Image Deep Mining on a Large-Scale Radiology Database for Automated Image Interpretation [article]

Hoo-Chang Shin, Le Lu, Lauren Kim, Ari Seff, Jianhua Yao, Ronald M. Summers
2015 arXiv   pre-print
We present an interleaved text/image deep learning system to extract and mine the semantic interactions of radiology images and reports from a national research hospital's Picture Archiving and Communication  ...  Our system interleaves between unsupervised learning and supervised learning on document- and sentence-level text collections, to generate semantic labels and to predict them given an image.  ...  We thank NVIDIA for the K40 GPU donation.  ... 
arXiv:1505.00670v1 fatcat:pwpfinxrh5hixl6rnjezaqci3e

Multiparametric prostate MRI and structured reporting: benefits and challenges in the PI-RADS era

Sanas Mir-Bashiri, Kaneschka Yaqubi, Piotr Woźnicki, Niklas Westhoff, Jost von Hardenberg, Thomas Huber, Matthias F. Froelich, Wieland H. Sommer, Maximilian F. Reiser, Stefan O. Schoenberg, Dominik Nörenberg
2021 Chinese Journal of Academic Radiology  
Combined with software-based solutions, structured radiology reports form the backbone to integrate results from radiomics analyses or AI-applications into radiological reports and vice versa.  ...  The PI-RADS (Prostate Imaging Reporting and Data System) 2.1 classification represents the classification system that is internationally recommended for MRI-based evaluation of clinically significant prostate  ...  represents an established semantic biomarker which can be extracted from radiological reports.  ... 
doi:10.1007/s42058-021-00059-1 fatcat:jecacrvirnab5gzr3citr3c2wy

Radiogenomics for Precision Medicine With A Big Data Analytics Perspective

Andreas S. Panayides, Marios Pattichis, Stephanos Leandrou, Costas Pitris, Anastasia Constantinidou, Constantinos S. Pattichis
2019 IEEE journal of biomedical and health informatics  
challenges from a big data analytics perspective, and discuss standardization and open data initiatives that will facilitate the adoption of precision medicine methods and practices.  ...  Using evidence-based substratification of patients, the objective is to achieve better prognosis, diagnosis, and treatment that will transform existing clinical pathways toward optimizing care for the  ...  Moreover, enhancement texture homogeneity feature [100] was further associated with larger lymph node status while irregularity feature was linked to smaller lymph node status.  ... 
doi:10.1109/jbhi.2018.2879381 pmid:30596591 fatcat:rqmjhmdmr5h3rdaody264ogs24

Deep learning in medical imaging and radiation therapy

Berkman Sahiner, Aria Pezeshk, Lubomir M. Hadjiiski, Xiaosong Wang, Karen Drukker, Kenny H. Cha, Ronald M. Summers, Maryellen L. Giger
2018 Medical Physics (Lancaster)  
for dataset expansion, and conclude by summarizing lessons learned, remaining challenges, and future directions.  ...  The goals of this review paper on deep learning (DL) in medical imaging and radiation therapy are to (a) summarize what has been achieved to date; (b) identify common and unique challenges, and strategies  ...  Zhang et al. 334 proposed a multimodal network that jointly learns from medical images and their diagnostic reports, in which semantic information interacts with visual information to improve the image  ... 
doi:10.1002/mp.13264 pmid:30367497 fatcat:bottst5mvrbkfedbuocbrstcnm

Integrating Digital Pens in Breast Imaging for Instant Knowledge Acquisition

Daniel Sonntag, Markus Weber, Alexander Cavallaro, Matthias Hammon
2014 The AI Magazine  
Our system imposes only minimal overhead on traditional form-filling processes and provides for a direct, ontology-based structuring of the user input for semantic search and retrieval applications, as  ...  Future radiology practices assume that the radiology reports should be uniform, comprehensive, and easily managed. This means that reports must be readable to humans and machines alike.  ...  We would also like to thank Daniel Gröger and Marcus Liwicki for their support in the technical realization of the penenabled form and the radiology team of the Image Science Institute in Erlangen, Germany  ... 
doi:10.1609/aimag.v35i1.2501 fatcat:nixbgkobbzgnjh3qgtoqcnlp3q

Multi-task weak supervision enables anatomically-resolved abnormality detection in whole-body FDG-PET/CT

Sabri Eyuboglu, Geoffrey Angus, Bhavik N. Patel, Anuj Pareek, Guido Davidzon, Jin Long, Jared Dunnmon, Matthew P. Lungren
2021 Nature Communications  
We demonstrate empirically that our multi-task representation is critical for strong performance on rare abnormalities with limited training data.  ...  Our framework automatically labels each region in a custom ontology of anatomical regions, providing a structured profile of the pathologies in each imaging exam.  ...  radiology PACS.  ... 
doi:10.1038/s41467-021-22018-1 pmid:33767174 fatcat:vko3koauunhgzodfxjjbek23gi

Automatic negation detection in narrative pathology reports

Ying Ou, Jon Patrick
2015 Artificial Intelligence in Medicine  
The application of rich feature sets provided useful clues for the classification of entity types.  ...  By feature engineering, the best feature configurations were attained, which boosted the F-scores significantly from 4.2% to 6.8% in 10-fold cross-validation experiments on the training sets.  ...  For example, assign number "1" for "apical lymph node is identified 4mm in diameter" and "single local lymph node".  ... 
doi:10.1016/j.artmed.2015.03.001 pmid:25990897 fatcat:yrijkncnsvht7lonmaqt7uyya4

Information from Searching Content with an Ontology-Utilizing Toolkit (iSCOUT)

Ronilda Lacson, Katherine P. Andriole, Luciano M. Prevedello, Ramin Khorasani
2012 Journal of digital imaging  
We developed and made publicly available a natural language processing toolkit, Information from Searching Content with an Ontology-Utilizing Toolkit (iSCOUT).  ...  We evaluated iSCOUT document retrieval of radiology reports that contained liver cysts, and compared precision and recall with and without using NCIT synonyms for query expansion. iSCOUT retrieved radiology  ...  A machine learning algorithm utilized for tumor status classification of MRI reports yielded mean precision and recall of 82.4% and 80.6%, respectively [29] .  ... 
doi:10.1007/s10278-012-9463-9 pmid:22349993 pmcid:PMC3389089 fatcat:b4ja3a5rincadbvqziffhi6s3u

A review of deep learning in medical imaging: Image traits, technology trends, case studies with progress highlights, and future promises [article]

S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos, James S. Duncan, Bram van Ginneken, Anant Madabhushi, Jerry L. Prince, Daniel Rueckert, Ronald M. Summers
2020 arXiv   pre-print
It is known that the success of AI is mostly attributed to the availability of big data with annotations for a single task and the advances in high performance computing.  ...  In this survey paper, we first highlight both clinical needs and technical challenges in medical imaging and describe how emerging trends in deep learning are addressing these issues.  ...  Other organs of interest to deep learning researchers include pancreas, lymph nodes and bowel.  ... 
arXiv:2008.09104v1 fatcat:z2gic7or4vgnnfcf4joimjha7i

ECR 2012 Book of Abstracts - A - Postergraduate Educational Programme

2012 Insights into Imaging  
To learn how to differentiate ischaemia from inflammation.  ...  The use of imaging probes based on different tracers with advanced high-resolution equipment allows viewing complex molecular and cellular structures.  ...  MRI is especially helpful for distinguishing stage IA from stage IB (≥ 50% myometrial invasion), which is associated with a 40% incidence of lymph node metastasis and a need for lymph node dissection and  ... 
doi:10.1007/s13244-012-0153-4 pmid:22696127 pmcid:PMC3481066 fatcat:te6ctbtakzh5njsw43geghw3ta

Machine Learning Techniques for Biomedical Natural Language Processing: A comprehensive Review

Essam H. Houssein, Rehab E. Mohamed, Abdelmgeid A. Ali
2021 IEEE Access  
This review discusses the current literature on the secondary use of electronic health record data for clinical research on chronic diseases and addresses the potential, challenges, and applications of  ...  Moreover, this review summarizes the utilizing of Deep Learning and Machine Learning techniques in biomedical NLP tasks based on chronic diseases related EHR data.  ...  Although regular expressions were more robust for extracting TNM (tumor characteristics (T), lymph node involvement (N), and tumor metastasis (M)) mentions, the used range of features used with the CRF  ... 
doi:10.1109/access.2021.3119621 fatcat:pl7h35nvqngk3gxpbdxvrgzg2u
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