These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
210 related articles for article (PubMed ID: 35934207)
21. Impact of deep learning reconstruction on intracranial 1.5 T magnetic resonance angiography. Yasaka K; Akai H; Sugawara H; Tajima T; Akahane M; Yoshioka N; Kabasawa H; Miyo R; Ohtomo K; Abe O; Kiryu S Jpn J Radiol; 2022 May; 40(5):476-483. PubMed ID: 34851499 [TBL] [Abstract][Full Text] [Related]
22. Compressed sensing and deep learning reconstruction for women's pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice. Ueda T; Ohno Y; Yamamoto K; Iwase A; Fukuba T; Hanamatsu S; Obama Y; Ikeda H; Ikedo M; Yui M; Murayama K; Toyama H Eur J Radiol; 2021 Jan; 134():109430. PubMed ID: 33276249 [TBL] [Abstract][Full Text] [Related]
23. Fast T2-Weighted Imaging With Deep Learning-Based Reconstruction: Evaluation of Image Quality and Diagnostic Performance in Patients Undergoing Radical Prostatectomy. Park JC; Park KJ; Park MY; Kim MH; Kim JK J Magn Reson Imaging; 2022 Jun; 55(6):1735-1744. PubMed ID: 34773449 [TBL] [Abstract][Full Text] [Related]
24. Acceleration of knee magnetic resonance imaging using a combination of compressed sensing and commercially available deep learning reconstruction: a preliminary study. Akai H; Yasaka K; Sugawara H; Tajima T; Kamitani M; Furuta T; Akahane M; Yoshioka N; Ohtomo K; Abe O; Kiryu S BMC Med Imaging; 2023 Jan; 23(1):5. PubMed ID: 36624404 [TBL] [Abstract][Full Text] [Related]
25. Clinical feasibility of deep learning reconstruction in liver diffusion-weighted imaging: Improvement of image quality and impact on apparent diffusion coefficient value. Chen Q; Fang S; Yuchen Y; Li R; Deng R; Chen Y; Ma D; Lin H; Yan F Eur J Radiol; 2023 Nov; 168():111149. PubMed ID: 37862927 [TBL] [Abstract][Full Text] [Related]
26. Deep Learning Reconstruction of Diffusion-weighted MRI Improves Image Quality for Prostatic Imaging. Ueda T; Ohno Y; Yamamoto K; Murayama K; Ikedo M; Yui M; Hanamatsu S; Tanaka Y; Obama Y; Ikeda H; Toyama H Radiology; 2022 May; 303(2):373-381. PubMed ID: 35103536 [TBL] [Abstract][Full Text] [Related]
27. Assessment of multi-modal magnetic resonance imaging for glioma based on a deep learning reconstruction approach with the denoising method. Sun J; Xu S; Guo Y; Ding J; Zhuo Z; Zhou D; Liu Y Acta Radiol; 2024 Oct; 65(10):1257-1264. PubMed ID: 39219486 [TBL] [Abstract][Full Text] [Related]
28. Deep learning reconstruction for 1.5 T cervical spine MRI: effect on interobserver agreement in the evaluation of degenerative changes. Yasaka K; Tanishima T; Ohtake Y; Tajima T; Akai H; Ohtomo K; Abe O; Kiryu S Eur Radiol; 2022 Sep; 32(9):6118-6125. PubMed ID: 35348861 [TBL] [Abstract][Full Text] [Related]
29. Ultra-High-Resolution T2-Weighted PROPELLER MRI of the Rectum With Deep Learning Reconstruction: Assessment of Image Quality and Diagnostic Performance. Matsumoto S; Tsuboyama T; Onishi H; Fukui H; Honda T; Wakayama T; Wang X; Matsui T; Nakamoto A; Ota T; Kiso K; Osawa K; Tomiyama N Invest Radiol; 2024 Jul; 59(7):479-488. PubMed ID: 37975732 [TBL] [Abstract][Full Text] [Related]
30. Bladder MRI with deep learning-based reconstruction: a prospective evaluation of muscle invasiveness using VI-RADS. Zhang X; Wang Y; Xu X; Zhang J; Sun Y; Hu M; Wang S; Li Y; Chen Y; Zhao X Abdom Radiol (NY); 2024 May; 49(5):1615-1625. PubMed ID: 38652125 [TBL] [Abstract][Full Text] [Related]
31. Deep-learning-based image quality enhancement of CT-like MR imaging in patients with suspected traumatic shoulder injury. Feuerriegel GC; Weiss K; Tu Van A; Leonhardt Y; Neumann J; Gassert FT; Haas Y; Schwarz M; Makowski MR; Woertler K; Karampinos DC; Gersing AS Eur J Radiol; 2024 Jan; 170():111246. PubMed ID: 38056345 [TBL] [Abstract][Full Text] [Related]
32. Rapid 3D breath-hold MR cholangiopancreatography using deep learning-constrained compressed sensing reconstruction. Zhang Y; Peng W; Xiao Y; Ming Y; Ma K; Hu S; Zeng W; Zeng L; Liang Z; Zhang X; Xia C; Li Z Eur Radiol; 2023 Apr; 33(4):2500-2509. PubMed ID: 36355200 [TBL] [Abstract][Full Text] [Related]
33. Application of deep learning-based image reconstruction in MR imaging of the shoulder joint to improve image quality and reduce scan time. Kaniewska M; Deininger-Czermak E; Getzmann JM; Wang X; Lohezic M; Guggenberger R Eur Radiol; 2023 Mar; 33(3):1513-1525. PubMed ID: 36166084 [TBL] [Abstract][Full Text] [Related]
34. Deep-learning-based reconstruction of T2-weighted magnetic resonance imaging of the prostate accelerated by compressed sensing provides improved image quality at half the acquisition time. Jurka M; Macova I; Wagnerova M; Capoun O; Jakubicek R; Ourednicek P; Lambert L; Burgetova A Quant Imaging Med Surg; 2024 May; 14(5):3534-3543. PubMed ID: 38720867 [TBL] [Abstract][Full Text] [Related]
35. Deep learning-based reconstruction for canine brain magnetic resonance imaging could improve image quality while reducing scan time. Choi H; Lee SK; Choi H; Lee Y; Lee K Vet Radiol Ultrasound; 2023 Sep; 64(5):873-880. PubMed ID: 37582510 [TBL] [Abstract][Full Text] [Related]
36. Improving Diagnostic Performance of MRI for Temporal Lobe Epilepsy With Deep Learning-Based Image Reconstruction in Patients With Suspected Focal Epilepsy. Suh PS; Park JE; Roh YH; Kim S; Jung M; Koo YS; Lee SA; Choi Y; Kim HS Korean J Radiol; 2024 Apr; 25(4):374-383. PubMed ID: 38528695 [TBL] [Abstract][Full Text] [Related]
37. Evaluation of late gadolinium enhancement cardiac MRI using deep learning reconstruction. Yang J; Wang F; Wang Z; Zhang W; Xie L; Wang L Acta Radiol; 2023 Oct; 64(10):2714-2721. PubMed ID: 37700572 [TBL] [Abstract][Full Text] [Related]
38. Clinical Impact of Deep Learning Reconstruction in MRI. Kiryu S; Akai H; Yasaka K; Tajima T; Kunimatsu A; Yoshioka N; Akahane M; Abe O; Ohtomo K Radiographics; 2023 Jun; 43(6):e220133. PubMed ID: 37200221 [TBL] [Abstract][Full Text] [Related]
39. Deep learning reconstruction for the evaluation of neuroforaminal stenosis using 1.5T cervical spine MRI: comparison with 3T MRI without deep learning reconstruction. Yasaka K; Tanishima T; Ohtake Y; Tajima T; Akai H; Ohtomo K; Abe O; Kiryu S Neuroradiology; 2022 Oct; 64(10):2077-2083. PubMed ID: 35918450 [TBL] [Abstract][Full Text] [Related]
40. Feasibility of high-resolution magnetic resonance imaging of the liver using deep learning reconstruction based on the deep learning denoising technique. Tanabe M; Higashi M; Yonezawa T; Yamaguchi T; Iida E; Furukawa M; Okada M; Shinoda K; Ito K Magn Reson Imaging; 2021 Jul; 80():121-126. PubMed ID: 33971240 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]