ArticleInternational journal of computer assisted radiology and surgery2017
Detection and grading of prostate cancer using temporal enhanced ultrasound: combining deep neural networks and tissue mimicking simulations.
Article in International journal of computer assisted radiology and surgery, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 49 citations in OpenAlex.
- Research on ultrasound-based radiomics: a bibliometric analysis.Quantitative imaging in medicine and surgery · 2024Article
- Systems Biology in Cancer Diagnosis Integrating Omics Technologies and Artificial Intelligence to Support Physician Decision Making.Journal of personalized medicine · 2023Review
- Automated Prediction of Osteoarthritis Level in Human Osteochondral Tissue Using Histopathological Images.Bioengineering (Basel, Switzerland) · 2023Article
- AI and professional liability assessment in healthcare. A revolution in legal medicine?Frontiers in medicine · 2023Review
- Towards targeted ultrasound-guided prostate biopsy by incorporating model and label uncertainty in cancer detection.International journal of computer assisted radiology and surgery · 2022Article
- Current status of deep learning applications in abdominal ultrasonography.Ultrasonography (Seoul, Korea) · 2021Article
- Deep Learning Assisted Detection of Abdominal Free Fluid in Morison's Pouch During Focused Assessment With Sonography in Trauma.Frontiers in medicine · 2021Article
- Deep adaptive registration of multi-modal prostate images.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2020Article
- Improving detection of prostate cancer foci via information fusion of MRI and temporal enhanced ultrasound.International journal of computer assisted radiology and surgery · 2020Article
- Artificial intelligence (AI) and big data in cancer and precision oncology.Computational and structural biotechnology journal · 2020Review
- Next generation diagnostic pathology: use of digital pathology and artificial intelligence tools to augment a pathological diagnosis.Diagnostic pathology · 2019Article
- Deep neural maps for unsupervised visualization of high-grade cancer in prostate biopsies.International journal of computer assisted radiology and surgery · 2019Article
- Artificial intelligence in cancer imaging: Clinical challenges and applications.CA: a cancer journal for clinicians · 2019Review
- Deep Recurrent Neural Networks for Prostate Cancer Detection: Analysis of Temporal Enhanced Ultrasound.IEEE transactions on medical imaging · 2018Article
- Toward a real-time system for temporal enhanced ultrasound-guided prostate biopsy.International journal of computer assisted radiology and surgery · 2018Article
- Optimize Transfer Learning for Lung Diseases in Bronchoscopy Using a New Concept: Sequential Fine-Tuning.IEEE journal of translational engineering in health and medicine · 2018Article
Corrections and comments
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Authors and funding
16 authors at 6 institutions in 3 countries.
Funding
Abstract
purposeTemporal Enhanced Ultrasound (TeUS) has been proposed as a new paradigm for tissue characterization based on a sequence of ultrasound radio frequency (RF) data. We previously used TeUS to successfully address the problem of prostate cancer detection in the fusion biopsies.
methodsIn this paper, we use TeUS to address the problem of grading prostate cancer in a clinical study of 197 biopsy cores from 132 patients. Our method involves capturing high-level latent features of TeUS with a deep learning approach followed by distribution learning to cluster aggressive cancer in a biopsy core. In this hypothesis-generating study, we utilize deep learning based feature visualization as a means to obtain insight into the physical phenomenon governing the interaction of temporal ultrasound with tissue.
resultsBased on the evidence derived from our feature visualization, and the structure of tissue from digital pathology, we build a simulation framework for studying the physical phenomenon underlying TeUS-based tissue characterization.
conclusionResults from simulation and feature visualization corroborated with the hypothesis that micro-vibrations of tissue microstructure, captured by low-frequency spectral features of TeUS, can be used for detection of prostate cancer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.