177 related articles for article (PubMed ID: 37164024)
1. Radiomic analysis for early differentiation of lung cancer recurrence from fibrosis in patients treated with lung stereotactic ablative radiotherapy.
Kunkyab T; Mou B; Jirasek A; Haston C; Andrews J; Thomas S; Hyde D
Phys Med Biol; 2023 Aug; 68(16):. PubMed ID: 37164024
[No Abstract] [Full Text] [Related]
2. Detection of Local Cancer Recurrence After Stereotactic Ablative Radiation Therapy for Lung Cancer: Physician Performance Versus Radiomic Assessment.
Mattonen SA; Palma DA; Johnson C; Louie AV; Landis M; Rodrigues G; Chan I; Etemad-Rezai R; Yeung TP; Senan S; Ward AD
Int J Radiat Oncol Biol Phys; 2016 Apr; 94(5):1121-8. PubMed ID: 26907916
[TBL] [Abstract][Full Text] [Related]
3. Pretreatment
Dissaux G; Visvikis D; Da-Ano R; Pradier O; Chajon E; Barillot I; Duvergé L; Masson I; Abgral R; Santiago Ribeiro MJ; Devillers A; Pallardy A; Fleury V; Mahé MA; De Crevoisier R; Hatt M; Schick U
J Nucl Med; 2020 Jun; 61(6):814-820. PubMed ID: 31732678
[TBL] [Abstract][Full Text] [Related]
4. Machine Learning Methods for Optimal Radiomics-Based Differentiation Between Recurrence and Inflammation: Application to Nasopharyngeal Carcinoma Post-therapy PET/CT Images.
Du D; Feng H; Lv W; Ashrafinia S; Yuan Q; Wang Q; Yang W; Feng Q; Chen W; Rahmim A; Lu L
Mol Imaging Biol; 2020 Jun; 22(3):730-738. PubMed ID: 31338709
[TBL] [Abstract][Full Text] [Related]
5. Differentiation of tumor recurrence from radiation-induced pulmonary fibrosis after stereotactic ablative radiotherapy for lung cancer: characterization of 18F-FDG PET/CT findings.
Nakajima N; Sugawara Y; Kataoka M; Hamamoto Y; Ochi T; Sakai S; Takahashi T; Kajihara M; Teramoto N; Yamashita M; Mochizuki T
Ann Nucl Med; 2013 Apr; 27(3):261-70. PubMed ID: 23299492
[TBL] [Abstract][Full Text] [Related]
6. Application and limitation of radiomics approach to prognostic prediction for lung stereotactic body radiotherapy using breath-hold CT images with random survival forest: A multi-institutional study.
Kakino R; Nakamura M; Mitsuyoshi T; Shintani T; Kokubo M; Negoro Y; Fushiki M; Ogura M; Itasaka S; Yamauchi C; Otsu S; Sakamoto T; Sakamoto M; Araki N; Hirashima H; Adachi T; Matsuo Y; Mizowaki T
Med Phys; 2020 Sep; 47(9):4634-4643. PubMed ID: 32645224
[TBL] [Abstract][Full Text] [Related]
7. Inconsistent CT NSCLC radiomics associated with feature selection methods, predictive models and related factors.
Ge G; Siddique A; Zhang J
Phys Med Biol; 2023 Jun; 68(12):. PubMed ID: 37072008
[No Abstract] [Full Text] [Related]
8. Machine learning-based radiomic analysis and growth visualization for ablation site recurrence diagnosis in follow-up CT.
Yin Y; de Haas RJ; Alves N; Pennings JP; Ruiter SJS; Kwee TC; Yakar D
Abdom Radiol (NY); 2024 Apr; 49(4):1122-1131. PubMed ID: 38289352
[TBL] [Abstract][Full Text] [Related]
9. A combined predictive model based on radiomics features and clinical factors for disease progression in early-stage non-small cell lung cancer treated with stereotactic ablative radiotherapy.
Yang H; Wang L; Shao G; Dong B; Wang F; Wei Y; Li P; Chen H; Chen W; Zheng Y; He Y; Zhao Y; Du X; Sun X; Wang Z; Wang Y; Zhou X; Lai X; Feng W; Shen L; Qiu G; Ji Y; Chen J; Jiang Y; Liu J; Zeng J; Wang C; Zhao Q; Yang X; Hu X; Ma H; Chen Q; Chen M; Jiang H; Xu Y
Front Oncol; 2022; 12():967360. PubMed ID: 35982975
[TBL] [Abstract][Full Text] [Related]
10. Distinguishing radiation fibrosis from tumour recurrence after stereotactic ablative radiotherapy (SABR) for lung cancer: a quantitative analysis of CT density changes.
Mattonen SA; Palma DA; Haasbeek CJ; Senan S; Ward AD
Acta Oncol; 2013 Jun; 52(5):910-8. PubMed ID: 23106174
[TBL] [Abstract][Full Text] [Related]
11. Machine Learning Radiomics Model for Early Identification of Small-Cell Lung Cancer on Computed Tomography Scans.
Shah RP; Selby HM; Mukherjee P; Verma S; Xie P; Xu Q; Das M; Malik S; Gevaert O; Napel S
JCO Clin Cancer Inform; 2021 Jun; 5():746-757. PubMed ID: 34264747
[TBL] [Abstract][Full Text] [Related]
12. Early prediction of tumor recurrence based on CT texture changes after stereotactic ablative radiotherapy (SABR) for lung cancer.
Mattonen SA; Palma DA; Haasbeek CJ; Senan S; Ward AD
Med Phys; 2014 Mar; 41(3):033502. PubMed ID: 24593744
[TBL] [Abstract][Full Text] [Related]
13. Histologic subtype classification of non-small cell lung cancer using PET/CT images.
Han Y; Ma Y; Wu Z; Zhang F; Zheng D; Liu X; Tao L; Liang Z; Yang Z; Li X; Huang J; Guo X
Eur J Nucl Med Mol Imaging; 2021 Feb; 48(2):350-360. PubMed ID: 32776232
[TBL] [Abstract][Full Text] [Related]
14. CT imaging features associated with recurrence in non-small cell lung cancer patients after stereotactic body radiotherapy.
Li Q; Kim J; Balagurunathan Y; Qi J; Liu Y; Latifi K; Moros EG; Schabath MB; Ye Z; Gillies RJ; Dilling TJ
Radiat Oncol; 2017 Sep; 12(1):158. PubMed ID: 28946909
[TBL] [Abstract][Full Text] [Related]
15. Preoperative prediction of vessel invasion in locally advanced gastric cancer based on computed tomography radiomics and machine learning.
Hu ZW; Liang P; Li ZL; Yong LL; Lu H; Wang R; Gao JB
Oncol Lett; 2023 Jul; 26(1):293. PubMed ID: 37274479
[TBL] [Abstract][Full Text] [Related]
16. Prediction of local recurrence and distant metastasis using radiomics analysis of pretreatment nasopharyngeal [18F]FDG PET/CT images.
Peng L; Hong X; Yuan Q; Lu L; Wang Q; Chen W
Ann Nucl Med; 2021 Apr; 35(4):458-468. PubMed ID: 33543393
[TBL] [Abstract][Full Text] [Related]
17. A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts ALK Rearrangement Status in Lung Adenocarcinoma.
Chang C; Sun X; Wang G; Yu H; Zhao W; Ge Y; Duan S; Qian X; Wang R; Lei B; Wang L; Liu L; Ruan M; Yan H; Liu C; Chen J; Xie W
Front Oncol; 2021; 11():603882. PubMed ID: 33738250
[TBL] [Abstract][Full Text] [Related]
18. Application of machine learning model to predict osteoporosis based on abdominal computed tomography images of the psoas muscle: a retrospective study.
Huang CB; Hu JS; Tan K; Zhang W; Xu TH; Yang L
BMC Geriatr; 2022 Oct; 22(1):796. PubMed ID: 36229793
[TBL] [Abstract][Full Text] [Related]
19. Associations of Radiomic Data Extracted from Static and Respiratory-Gated CT Scans with Disease Recurrence in Lung Cancer Patients Treated with SBRT.
Huynh E; Coroller TP; Narayan V; Agrawal V; Romano J; Franco I; Parmar C; Hou Y; Mak RH; Aerts HJ
PLoS One; 2017; 12(1):e0169172. PubMed ID: 28046060
[TBL] [Abstract][Full Text] [Related]
20. Combining computed tomography and biologically effective dose in radiomics and deep learning improves prediction of tumor response to robotic lung stereotactic body radiation therapy.
Avanzo M; Gagliardi V; Stancanello J; Blanck O; Pirrone G; El Naqa I; Revelant A; Sartor G
Med Phys; 2021 Oct; 48(10):6257-6269. PubMed ID: 34415574
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]