266 related articles for article (PubMed ID: 31011772)
1. Preoperative evaluation of tumour consistency in pituitary macroadenomas: a machine learning-based histogram analysis on conventional T2-weighted MRI.
Zeynalova A; Kocak B; Durmaz ES; Comunoglu N; Ozcan K; Ozcan G; Turk O; Tanriover N; Kocer N; Kizilkilic O; Islak C
Neuroradiology; 2019 Jul; 61(7):767-774. PubMed ID: 31011772
[TBL] [Abstract][Full Text] [Related]
2. Prediction of pituitary adenoma surgical consistency: radiomic data mining and machine learning on T2-weighted MRI.
Cuocolo R; Ugga L; Solari D; Corvino S; D'Amico A; Russo D; Cappabianca P; Cavallo LM; Elefante A
Neuroradiology; 2020 Dec; 62(12):1649-1656. PubMed ID: 32705290
[TBL] [Abstract][Full Text] [Related]
3. Predicting response to somatostatin analogues in acromegaly: machine learning-based high-dimensional quantitative texture analysis on T2-weighted MRI.
Kocak B; Durmaz ES; Kadioglu P; Polat Korkmaz O; Comunoglu N; Tanriover N; Kocer N; Islak C; Kizilkilic O
Eur Radiol; 2019 Jun; 29(6):2731-2739. PubMed ID: 30506213
[TBL] [Abstract][Full Text] [Related]
4. A machine learning model to precisely immunohistochemically classify pituitary adenoma subtypes with radiomics based on preoperative magnetic resonance imaging.
Peng A; Dai H; Duan H; Chen Y; Huang J; Zhou L; Chen L
Eur J Radiol; 2020 Apr; 125():108892. PubMed ID: 32087466
[TBL] [Abstract][Full Text] [Related]
5. Prediction of high proliferative index in pituitary macroadenomas using MRI-based radiomics and machine learning.
Ugga L; Cuocolo R; Solari D; Guadagno E; D'Amico A; Somma T; Cappabianca P; Del Basso de Caro ML; Cavallo LM; Brunetti A
Neuroradiology; 2019 Dec; 61(12):1365-1373. PubMed ID: 31375883
[TBL] [Abstract][Full Text] [Related]
6. Radiogenomics of lower-grade gliomas: machine learning-based MRI texture analysis for predicting 1p/19q codeletion status.
Kocak B; Durmaz ES; Ates E; Sel I; Turgut Gunes S; Kaya OK; Zeynalova A; Kilickesmez O
Eur Radiol; 2020 Feb; 30(2):877-886. PubMed ID: 31691122
[TBL] [Abstract][Full Text] [Related]
7. MR textural analysis on contrast enhanced 3D-SPACE images in assessment of consistency of pituitary macroadenoma.
Rui W; Wu Y; Ma Z; Wang Y; Wang Y; Xu X; Zhang J; Yao Z
Eur J Radiol; 2019 Jan; 110():219-224. PubMed ID: 30599863
[TBL] [Abstract][Full Text] [Related]
8. Texture Analysis of High b-Value Diffusion-Weighted Imaging for Evaluating Consistency of Pituitary Macroadenomas.
Su CQ; Zhang X; Pan T; Chen XT; Chen W; Duan SF; Ji J; Hu WX; Lu SS; Hong XN
J Magn Reson Imaging; 2020 May; 51(5):1507-1513. PubMed ID: 31769565
[TBL] [Abstract][Full Text] [Related]
9. Prediction of the consistency of pituitary adenoma: A comparative study on diffusion-weighted imaging and pathological results.
Yiping L; Ji X; Daoying G; Bo Y
J Neuroradiol; 2016 Jun; 43(3):186-94. PubMed ID: 26585529
[TBL] [Abstract][Full Text] [Related]
10. Radiomic Features on Multiparametric MRI for Preoperative Evaluation of Pituitary Macroadenomas Consistency: Preliminary Findings.
Wan T; Wu C; Meng M; Liu T; Li C; Ma J; Qin Z
J Magn Reson Imaging; 2022 May; 55(5):1491-1503. PubMed ID: 34549842
[TBL] [Abstract][Full Text] [Related]
11. Radiomic analysis of preoperative magnetic resonance imaging for the prediction of pituitary adenoma consistency.
Mendi BAR; Batur H; Çay N; Çakır BT
Acta Radiol; 2023 Aug; 64(8):2470-2478. PubMed ID: 37170546
[TBL] [Abstract][Full Text] [Related]
12. Pituitary macroadenoma: Accuracy of apparent diffusion coefficient magnetic resonance imaging in grading tumor aggressiveness.
Doai M; Tonami H; Matoba M; Tachibana O; Iizuka H; Nakada S; Yamada S
Neuroradiol J; 2019 Apr; 32(2):86-91. PubMed ID: 30648472
[TBL] [Abstract][Full Text] [Related]
13. Relationship Between Pituitary Adenoma Consistency and Extent of Resection Based on Tumor/Cerebellar Peduncle T2-Weighted Imaging Intensity (TCTI) Ratio of the Point on Preoperative Magnetic Resonance Imaging (MRI) Corresponding to the Residual Point on Postoperative MRI.
Chen XY; Ding CY; You HH; Chen JY; Jiang CZ; Yan XR; Lin ZY; Kang DZ
Med Sci Monit; 2020 Jan; 26():e919565. PubMed ID: 31904008
[TBL] [Abstract][Full Text] [Related]
14. MR-Based Radiomics for Differential Diagnosis between Cystic Pituitary Adenoma and Rathke Cleft Cyst.
Wang Y; Chen S; Shi F; Cheng X; Xu Q; Li J; Luo S; Jiang P; Wei Y; Zhou C; Zheng L; Xia K; Lu G; Zhang Z
Comput Math Methods Med; 2021; 2021():6438861. PubMed ID: 34422095
[TBL] [Abstract][Full Text] [Related]
15. Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.
Romeo V; Maurea S; Cuocolo R; Petretta M; Mainenti PP; Verde F; Coppola M; Dell'Aversana S; Brunetti A
J Magn Reson Imaging; 2018 Jul; 48(1):198-204. PubMed ID: 29341325
[TBL] [Abstract][Full Text] [Related]
16. Analysis of 7-tesla diffusion-weighted imaging in the prediction of pituitary macroadenoma consistency.
Rutland JW; Loewenstern J; Ranti D; Tsankova NM; Bellaire CP; Bederson JB; Delman BN; Shrivastava RK; Balchandani P
J Neurosurg; 2020 Feb; 134(3):771-779. PubMed ID: 32109870
[TBL] [Abstract][Full Text] [Related]
17. Pituitary adenoma consistency: Direct correlation of ultrahigh field 7T MRI with histopathological analysis.
Yao A; Rutland JW; Verma G; Banihashemi A; Padormo F; Tsankova NM; Delman BN; Shrivastava RK; Balchandani P
Eur J Radiol; 2020 May; 126():108931. PubMed ID: 32146344
[TBL] [Abstract][Full Text] [Related]
18. Non-invasive radiomics approach potentially predicts non-functioning pituitary adenomas subtypes before surgery.
Zhang S; Song G; Zang Y; Jia J; Wang C; Li C; Tian J; Dong D; Zhang Y
Eur Radiol; 2018 Sep; 28(9):3692-3701. PubMed ID: 29572634
[TBL] [Abstract][Full Text] [Related]
19. Development and Evaluation of Deep Learning-based Automated Segmentation of Pituitary Adenoma in Clinical Task.
Wang H; Zhang W; Li S; Fan Y; Feng M; Wang R
J Clin Endocrinol Metab; 2021 Aug; 106(9):2535-2546. PubMed ID: 34060609
[TBL] [Abstract][Full Text] [Related]
20. Thin-Slice Pituitary MRI with Deep Learning-based Reconstruction: Diagnostic Performance in a Postoperative Setting.
Kim M; Kim HS; Kim HJ; Park JE; Park SY; Kim YH; Kim SJ; Lee J; Lebel MR
Radiology; 2021 Jan; 298(1):114-122. PubMed ID: 33141001
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]