radiomics tools package Search Results


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COMSOL Inc multiphysics 5.5 software package
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COMSOL Inc comsol multiphysics 5.5
Comsol Multiphysics 5.5, supplied by COMSOL Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Cst Microwave Studio (Mws) Software Package, supplied by Dassault Systemes, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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MathWorks Inc matlab-based radiomics tools package
Matlab Based Radiomics Tools Package, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Cell Signaling Technology Inc electromagnetic software package cst microwave studio
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Siemens Healthineers radiomics 1.0.9a
Pipeline step diagram of machine learning-derived <t>radiomics.</t>
Radiomics 1.0.9a, supplied by Siemens Healthineers, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Cell Signaling Technology Inc microwave studio (mws) software package
Pipeline step diagram of machine learning-derived <t>radiomics.</t>
Microwave Studio (Mws) Software Package, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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COMSOL Inc radio frequency module of comsol multiphysics 5.4 software package
Pipeline step diagram of machine learning-derived <t>radiomics.</t>
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Cell Signaling Technology Inc studio suite 2016 microwave studio software package
Pipeline step diagram of machine learning-derived <t>radiomics.</t>
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MathWorks Inc radiomics tool package matlab 2024a
Pipeline step diagram of machine learning-derived <t>radiomics.</t>
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Image Search Results


Pipeline step diagram of machine learning-derived radiomics.

Journal: Cancers

Article Title: Simultaneous Identification of EGFR, KRAS, ERBB2, and TP53 Mutations in Patients with Non-Small Cell Lung Cancer by Machine Learning-Derived Three-Dimensional Radiomics

doi: 10.3390/cancers13081814

Figure Lengend Snippet: Pipeline step diagram of machine learning-derived radiomics.

Article Snippet: One radiologist with 18 years of experience in diagnostic imaging, who was blinded to the results of the NGS test, performed semi-automated three-dimensional (3D) tumor segmentation, using a radiomics analysis software package (Radiomics 1.0.9a, Siemens Healthineers) on a research platform (SyngoVia VB10b, Research Frontier, Siemens Healthineers).

Techniques: Derivative Assay

Receiver operating characteristic curves for discriminating mutations by the radiomics model and combined model (radiomic features and clinical factors).

Journal: Cancers

Article Title: Simultaneous Identification of EGFR, KRAS, ERBB2, and TP53 Mutations in Patients with Non-Small Cell Lung Cancer by Machine Learning-Derived Three-Dimensional Radiomics

doi: 10.3390/cancers13081814

Figure Lengend Snippet: Receiver operating characteristic curves for discriminating mutations by the radiomics model and combined model (radiomic features and clinical factors).

Article Snippet: One radiologist with 18 years of experience in diagnostic imaging, who was blinded to the results of the NGS test, performed semi-automated three-dimensional (3D) tumor segmentation, using a radiomics analysis software package (Radiomics 1.0.9a, Siemens Healthineers) on a research platform (SyngoVia VB10b, Research Frontier, Siemens Healthineers).

Techniques:

Representative CT images with tumor segmentation by a radiomics analysis platform. ( A ) A 30-year-old female non-smoker, with EGFR mutation in lung adenocarcinoma. A lobulated solid mass is observed in the lower lobe of the right lung. The maximum diameter is 23 mm. ( B ) A 64-year-old male smoker, with KRAS mutation in lung adenocarcinoma. A solid mass with rough margin is observed in the upper lobe of the left lung. The maximum diameter is 10 mm. ( C ) A 74 year-old female non-smoker, with ERBB2 mutation in lung adenocarcinoma. A lobulated solid mass is observed in the middle lobe of the right lung. The maximum diameter is 18 mm. ( D ) A 66-year-old male smoker, with TP53 mutation in lung adenocarcinoma. A lobulated solid mass with rough margin is observed in the lower lobe of the right lung. The maximum diameter is 12 mm.

Journal: Cancers

Article Title: Simultaneous Identification of EGFR, KRAS, ERBB2, and TP53 Mutations in Patients with Non-Small Cell Lung Cancer by Machine Learning-Derived Three-Dimensional Radiomics

doi: 10.3390/cancers13081814

Figure Lengend Snippet: Representative CT images with tumor segmentation by a radiomics analysis platform. ( A ) A 30-year-old female non-smoker, with EGFR mutation in lung adenocarcinoma. A lobulated solid mass is observed in the lower lobe of the right lung. The maximum diameter is 23 mm. ( B ) A 64-year-old male smoker, with KRAS mutation in lung adenocarcinoma. A solid mass with rough margin is observed in the upper lobe of the left lung. The maximum diameter is 10 mm. ( C ) A 74 year-old female non-smoker, with ERBB2 mutation in lung adenocarcinoma. A lobulated solid mass is observed in the middle lobe of the right lung. The maximum diameter is 18 mm. ( D ) A 66-year-old male smoker, with TP53 mutation in lung adenocarcinoma. A lobulated solid mass with rough margin is observed in the lower lobe of the right lung. The maximum diameter is 12 mm.

Article Snippet: One radiologist with 18 years of experience in diagnostic imaging, who was blinded to the results of the NGS test, performed semi-automated three-dimensional (3D) tumor segmentation, using a radiomics analysis software package (Radiomics 1.0.9a, Siemens Healthineers) on a research platform (SyngoVia VB10b, Research Frontier, Siemens Healthineers).

Techniques: Mutagenesis