189 related articles for article (PubMed ID: 36978182)
1. Tumor-to-bone distance and radiomic features on MRI distinguish intramuscular lipomas from well-differentiated liposarcomas.
Sudjai N; Siriwanarangsun P; Lektrakul N; Saiviroonporn P; Maungsomboon S; Phimolsarnti R; Asavamongkolkul A; Chandhanayingyong C
J Orthop Surg Res; 2023 Mar; 18(1):255. PubMed ID: 36978182
[TBL] [Abstract][Full Text] [Related]
2. Differentiation Between Lipomas and Atypical Lipomatous Tumors of the Extremities Using Radiomics.
Tang Y; Cui J; Zhu J; Fan G
J Magn Reson Imaging; 2022 Dec; 56(6):1746-1754. PubMed ID: 35348280
[TBL] [Abstract][Full Text] [Related]
3. Radiomics approach to distinguish between well differentiated liposarcomas and lipomas on MRI.
Vos M; Starmans MPA; Timbergen MJM; van der Voort SR; Padmos GA; Kessels W; Niessen WJ; van Leenders GJLH; Grünhagen DJ; Sleijfer S; Verhoef C; Klein S; Visser JJ
Br J Surg; 2019 Dec; 106(13):1800-1809. PubMed ID: 31747074
[TBL] [Abstract][Full Text] [Related]
4. Radiomics and Machine Learning Differentiate Soft-Tissue Lipoma and Liposarcoma Better than Musculoskeletal Radiologists.
Malinauskaite I; Hofmeister J; Burgermeister S; Neroladaki A; Hamard M; Montet X; Boudabbous S
Sarcoma; 2020; 2020():7163453. PubMed ID: 31997918
[TBL] [Abstract][Full Text] [Related]
5. Developing a clinical scoring system to differentiate deep-seated atypical lipomatous tumor from lipoma of soft tissue.
Cheng Y; Ko AT; Huang JH; Lee BC; Yang RS; Liang CW; Tai HC; Cheng NC
Asian J Surg; 2019 Aug; 42(8):832-838. PubMed ID: 30711441
[TBL] [Abstract][Full Text] [Related]
6. Discrimination of lipoma from atypical lipomatous tumor/well-differentiated liposarcoma using magnetic resonance imaging radiomics combined with machine learning.
Cay N; Mendi BAR; Batur H; Erdogan F
Jpn J Radiol; 2022 Sep; 40(9):951-960. PubMed ID: 35430677
[TBL] [Abstract][Full Text] [Related]
7. MRI-based radiomics to predict lipomatous soft tissue tumors malignancy: a pilot study.
Leporq B; Bouhamama A; Pilleul F; Lame F; Bihane C; Sdika M; Blay JY; Beuf O
Cancer Imaging; 2020 Oct; 20(1):78. PubMed ID: 33115533
[TBL] [Abstract][Full Text] [Related]
8. Differentiation of lipoma from liposarcoma on MRI using texture and shape analysis.
Thornhill RE; Golfam M; Sheikh A; Cron GO; White EA; Werier J; Schweitzer ME; Di Primio G
Acad Radiol; 2014 Sep; 21(9):1185-94. PubMed ID: 25107867
[TBL] [Abstract][Full Text] [Related]
9. Differentiating atypical lipomatous tumors from lipomas with magnetic resonance imaging: a comparison with MDM2 gene amplification status.
Knebel C; Neumann J; Schwaiger BJ; Karampinos DC; Pfeiffer D; Specht K; Lenze U; von Eisenhart-Rothe R; Rummeny EJ; Woertler K; Gersing AS
BMC Cancer; 2019 Apr; 19(1):309. PubMed ID: 30943944
[TBL] [Abstract][Full Text] [Related]
10. Radiomics-based approaches outperform visual analysis for differentiating lipoma from atypical lipomatous tumors: a review.
Haidey J; Low G; Wilson MP
Skeletal Radiol; 2023 Jun; 52(6):1089-1100. PubMed ID: 36385583
[TBL] [Abstract][Full Text] [Related]
11. MRI radiomics-based machine learning for classification of deep-seated lipoma and atypical lipomatous tumor of the extremities.
Gitto S; Interlenghi M; Cuocolo R; Salvatore C; Giannetta V; Badalyan J; Gallazzi E; Spinelli MS; Gallazzi M; Serpi F; Messina C; Albano D; Annovazzi A; Anelli V; Baldi J; Aliprandi A; Armiraglio E; Parafioriti A; Daolio PA; Luzzati A; Biagini R; Castiglioni I; Sconfienza LM
Radiol Med; 2023 Aug; 128(8):989-998. PubMed ID: 37335422
[TBL] [Abstract][Full Text] [Related]
12. Diagnostic accuracy of CT and MR features for detecting atypical lipomatous tumors and malignant liposarcomas: a systematic review and meta-analysis.
Wilson MP; Haidey J; Murad MH; Sept L; Low G
Eur Radiol; 2023 Dec; 33(12):8605-8616. PubMed ID: 37439933
[TBL] [Abstract][Full Text] [Related]
13. Development and evaluation of machine learning models based on X-ray radiomics for the classification and differentiation of malignant and benign bone tumors.
von Schacky CE; Wilhelm NJ; Schäfer VS; Leonhardt Y; Jung M; Jungmann PM; Russe MF; Foreman SC; Gassert FG; Gassert FT; Schwaiger BJ; Mogler C; Knebel C; von Eisenhart-Rothe R; Makowski MR; Woertler K; Burgkart R; Gersing AS
Eur Radiol; 2022 Sep; 32(9):6247-6257. PubMed ID: 35396665
[TBL] [Abstract][Full Text] [Related]
14. Machine Learning Diagnosis of Small-Bowel Crohn Disease Using T2-Weighted MRI Radiomic and Clinical Data.
Liu RX; Li H; Towbin AJ; Ata NA; Smith EA; Tkach JA; Denson LA; He L; Dillman JR
AJR Am J Roentgenol; 2024 Jan; 222(1):e2329812. PubMed ID: 37530398
[No Abstract] [Full Text] [Related]
15. MRI radiomics-based machine-learning classification of bone chondrosarcoma.
Gitto S; Cuocolo R; Albano D; Chianca V; Messina C; Gambino A; Ugga L; Cortese MC; Lazzara A; Ricci D; Spairani R; Zanchetta E; Luzzati A; Brunetti A; Parafioriti A; Sconfienza LM
Eur J Radiol; 2020 Jul; 128():109043. PubMed ID: 32438261
[TBL] [Abstract][Full Text] [Related]
16. Novel computer aided diagnostic models on multimodality medical images to differentiate well differentiated liposarcomas from lipomas approached by deep learning methods.
Yang Y; Zhou Y; Zhou C; Ma X
Orphanet J Rare Dis; 2022 Apr; 17(1):158. PubMed ID: 35392952
[TBL] [Abstract][Full Text] [Related]
17. Quantitative signal intensity ratios to distinguish between subfascial lipoma and atypical lipomatous tumor/well-differentiated liposarcoma using short-tau inversion recovery (STIR) MRI.
Donners R; Krieg AH; Baumhoer D; Boll DT; Harder D
Diagn Interv Imaging; 2020 Jun; 101(6):383-390. PubMed ID: 32107197
[TBL] [Abstract][Full Text] [Related]
18. An MRI-based decision tree to distinguish lipomas and lipoma variants from well-differentiated liposarcoma of the extremity and superficial trunk: Classification and regression tree (CART) analysis.
Shim EJ; Yoon MA; Yoo HJ; Chee CG; Lee MH; Lee SH; Chung HW; Shin MJ
Eur J Radiol; 2020 Jun; 127():109012. PubMed ID: 32339981
[TBL] [Abstract][Full Text] [Related]
19. Diffusion-weighted MRI radiomics of spine bone tumors: feature stability and machine learning-based classification performance.
Gitto S; Bologna M; Corino VDA; Emili I; Albano D; Messina C; Armiraglio E; Parafioriti A; Luzzati A; Mainardi L; Sconfienza LM
Radiol Med; 2022 May; 127(5):518-525. PubMed ID: 35320464
[TBL] [Abstract][Full Text] [Related]
20. A Triple-Classification Radiomics Model for the Differentiation of Primary Chordoma, Giant Cell Tumor, and Metastatic Tumor of Sacrum Based on T2-Weighted and Contrast-Enhanced T1-Weighted MRI.
Yin P; Mao N; Zhao C; Wu J; Chen L; Hong N
J Magn Reson Imaging; 2019 Mar; 49(3):752-759. PubMed ID: 30430686
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
