Eisuke Fukuma
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Eisuke Fukuma has a total of 15 co-authors. Here are the top co-authors by number of shared publications:
- Youichi Machida
Kameda Medical Center, Department of Radiology, Chiba 296-0041, Japan
2 shared publications - Ai Saita
Kameda Kyobashi Clinic, Tokyo Square Garden 4F, 3-1-1 Kyobashi, Chuo City, Tokyo 104-0031 Japan
1 shared publication Akiko Shimauchi
Department of Radiology, Kameda Kyobashi Clinic, 3-1-1 Kyobashi, Chuo Ward, Tokyo 104-0031, Japan
1 shared publication- Amy Deipolyi
Charleston Area Medical Center, Vascular Center of Excellence, 3200 MacCorkle Ave SE, Charleston, WV 25304
1 shared publication - Dania Daye
Division of Interventional Radiology, Department of Radiology, Massachusetts General Hospital
1 shared publication - Daniel R. Gomez
Memorial Sloan Kettering Cancer Center
1 shared publication
Latest Publications
- 1 June 2019
- Published by Elsevier in Academic Radiology
- Vol. 26 (6) , 744-751
MRI Findings After Cryoablation of Primary Breast Cancer Without Surgical Resection
- 1 June 2019
- Published by Elsevier in Academic Radiology
- Vol. 26 (6) , 744-751
MRI Findings After Cryoablation of Primary Breast Cancer Without Surgical Resection
- 22 June 2016
- Published by Springer Nature
- p. 183-198
Ultrasonography Guided Nonsurgical Cryoablation for Small Breast Cancer
- 22 June 2016
- Published by Springer Nature
- p. 183-198
Ultrasonography Guided Nonsurgical Cryoablation for Small Breast Cancer
- Open Access
- 18 June 2016
- Published by Springer Nature in SpringerPlus
- Vol. 5 (1) , 780
Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version
A new software version of VolparaDensity (Volpara Algorithm version 1.5.1) is capable of calculating volumetric breast density (VBD) using either full-field digital mammography (FFDM) or digital breast tomosynthesis (DBT) images. In this preliminary study, we evaluated the feasibility and consistency of this new automated software. Raw data from both DBT and FFDM were acquired from women breast cancer screening at our institution between April and August 2015 using. The DBT and FFDM images obtained under a single compression were collected and VBD was measured using fully automated software. A paired t test was used to analyze differences in the VBD calculated from paired FFDM and DBT images. The correlation coefficient (R value) was calculated and p < 0.05 was considered significant. Dualmodality images were acquired in 160 women; VBD data were available for all but one. There was a significant difference in the VBD of individual breasts calculated from DBT and FFDM and when data were compared per case (<0.001 and p = 0.006, respectively). There were very good to excellent correlations between data from FFDM and from DBT (R = 0.78, p < 0.0001; per breast, R = 0.89, p < 0.0001, per case, R = 0.91, p < 0.0001). VBD from DBT was well correlated to that from FFDM, though significant differences were observed between the two.
- 18 June 2016
- Published by Springer Nature in SpringerPlus
- Vol. 5 (1) , 780
Open AccessAutomated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version
A new software version of VolparaDensity (Volpara Algorithm version 1.5.1) is capable of calculating volumetric breast density (VBD) using either full-field digital mammography (FFDM) or digital breast tomosynthesis (DBT) images. In this preliminary study, we evaluated the feasibility and consistency of this new automated software. Raw data from both DBT and FFDM were acquired from women breast cancer screening at our institution between April and August 2015 using. The DBT and FFDM images obtained under a single compression were collected and VBD was measured using fully automated software. A paired t test was used to analyze differences in the VBD calculated from paired FFDM and DBT images. The correlation coefficient (R value) was calculated and p < 0.05 was considered significant. Dualmodality images were acquired in 160 women; VBD data were available for all but one. There was a significant difference in the VBD of individual breasts calculated from DBT and FFDM and when data were compared per case (<0.001 and p = 0.006, respectively). There were very good to excellent correlations between data from FFDM and from DBT (R = 0.78, p < 0.0001; per breast, R = 0.89, p < 0.0001, per case, R = 0.91, p < 0.0001). VBD from DBT was well correlated to that from FFDM, though significant differences were observed between the two.