LEADER 06141nam 2200757 450 001 996344046903316 005 20200106101458.0 010 $a0-7503-2539-9 010 $a0-7503-2540-2 024 7 $a10.1088/978-0-7503-2540-0 035 $a(CKB)5280000000206801 035 $a(CaBNVSL)thg00979913 035 $a(OCoLC)1135509878 035 $a(IOP)9780750325400 035 $a(EXLCZ)995280000000206801 100 $a20200106d2020 uy 0 101 0 $aeng 135 $aurcn||||m|||a 181 $2rdacontent 182 $2isbdmedia 183 $2rdacarrier 200 00$aLung cancer and imaging /$fedited by Ayman El-Baz, Jasjit S. Suri 210 1$aBristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) :$cIOP Publishing,$d[2020] 215 $a1 online resource (various pagings) $cillustrations (some color) 225 1 $aIOP ebooks. [2020 collection] 225 1 $aIPEM-IOP series in physics and engineering in medicine and biology 300 $a"Version: 20191201"--Title page verso. 311 $a0-7503-2538-0 320 $aIncludes bibliographical references. 327 $a1. Early diagnosis system for lung nodules based on the integration of a higher-order MGRF appearance feature model and 3D-CNN -- 1.1. Introduction -- 1.2. Methods -- 1.3. Experimental results -- 1.4. Conclusion 327 $a2. Capsule networks for lung cancer screening -- 2.1. Introduction -- 2.2. Capsule network -- 2.3. Fast capsule network -- 2.4. Dataset -- 2.5. Experiments -- 2.6. Results and discussion -- 2.7. Conclusions 327 $a3. Quantitative malignancy recognition of lung cancer using non-invasive image modalities -- 3.1. Introduction -- 3.2. Materials and methods -- 3.3. Conclusion 327 $a4. Epidemiology of lung cancer -- 4.1. Descriptive epidemiology of lung cancer -- 4.2. Risk factors of lung cancer -- 4.3. Lung cancer in never-smokers -- 4.4. Screening -- 4.5. Conclusion 327 $a5. Use of biomarkers in lung cancer diagnosis, prognosis, and treatment -- 5.1. Introduction -- 5.2. Histological subtypes and respective personalized medicine -- 5.3. Available screening assays to detect molecular alterations and genetic rearrangements -- 5.4. Molecular methods used to detect mutations -- 5.5. Genomic markers -- 5.6. Proteomic markers -- 5.7. Metabolic markers -- 5.8. Immunotherapy markers -- 5.9. The emerging role of microRNAs -- 5.10. Clinical trials with targetable oncogenic drivers -- 5.11. Conclusion 327 $a6. Radiomics and lung cancer : promising news for early detection of nodules -- 6.1. Introduction -- 6.2. Interpretation of small lung nodules -- 6.3. Computer-aided detection/diagnosis (CAD) -- 6.4. Radiomics -- 6.5. Conclusion 327 $a7. Photodynamic diagnosis and treatment of lung cancer -- 7.1. Introduction -- 7.2. Cancer -- 7.3. Photodynamic diagnosis -- 7.4. Photodynamic therapy -- 7.5. Conclusion 327 $a8. Cold atmospheric plasma and iron oxide based magnetic nanoparticles for synergetic lung cancer therapy -- 8.1. Introduction -- 8.2. Therapeutic effect of cold atmospheric plasma in lung cancer -- 8.3. The therapeutic effect of magnetic iron oxide nanoparticles in lung cancer -- 8.4. Synergistic therapeutic effects of cold atmospheric plasma and magnetic iron oxide nanoparticles in lung cancer -- 8.5. The synergistic therapeutic effect of cold atmospheric plasma and drug-loaded magnetic nanoparticles in lung cancer -- 8.6. Conclusions 327 $a9. Exploiting exhaled aerosol fingerprints to detect lung cancers and obstructive respiratory diseases -- 9.1. Introduction -- 9.2. Methods and materials -- 9.3. Results -- 9.4. Discussion -- 9.5. Conclusion 327 $a10. A study of ground-glass opacity (GGO) nodules in the automated detection of lung cancer -- 10.1. Introduction -- 10.2. Ground-glass opacity (GGO) nodules -- 10.3. Computer-aided detection of GGO nodules -- 10.4. Different ways to handle GGOs in automated detection -- 10.5. Conclusion 327 $a11. Electromagnetic imaging and lung ablation -- 11.1. Introduction -- 11.2. Electrical impedance tomography -- 11.3. Magnetic induction tomography -- 11.4. Microwave imaging -- 11.5. Lung ablation -- 11.6. Current trends and future perspectives -- 11.7. Conclusion. 330 3 $aLung cancer is one of the most common cancers in both men and women worldwide. Early diagnosis of lung cancer can significantly increase the chances of a patient's survival, yet early detection has historically been difficult. As a result, there has been a great deal of progress in the development of accurate and fast diagnostic tools in recent years. Lung Cancer and Imaging provides an introduction to both the methods currently used in lung cancer diagnosis and the promising new techniques that are emerging. Areas covered include the major trends and challenges in lung cancer detection and diagnosis, classification of cancer types, lung feature extraction in joint PET/CT images, and algorithms in the area of low dosage CT lung cancer images. Part of Series in Physics and Engineering in Medicine and Biology. 410 0$aIOP ebooks.$p2020 collection. 410 0$aIPEM-IOP series in physics and engineering in medicine and biology. 606 $aLungs$xCancer$xImaging 606 $aLung Neoplasms$xdiagnostic imaging 606 $aRadiography 606 $aDiagnostic Imaging$xmethods 606 $aMedical imaging$2bicssc 606 $aMEDICAL / Allied Health Services / Imaging Technologies$2bisacsh 615 0$aLungs$xCancer$xImaging. 615 12$aLung Neoplasms$xdiagnostic imaging. 615 12$aRadiography. 615 22$aDiagnostic Imaging$xmethods. 615 7$aMedical imaging. 615 7$aMEDICAL / Allied Health Services / Imaging Technologies. 676 $a616.99/424075 702 $aEl-Baz$b Ayman S. 702 $aSuri$b Jasjit S. 712 02$aInstitute of Physics (Great Britain), 801 0$bCaBNVSL 801 1$bCaBNVSL 801 2$bCaBNVSL 906 $aBOOK 912 $a996344046903316 996 $aLung cancer and imaging$92554164 997 $aUNISA