ImplicitVol: Sensorless 3D Ultrasound Reconstruction with Deep Implicit Representation

Chen, M.L., Chang, C.H., Yu, C.H., Cheng, Y.C., Chang, F.M.: Prenatal diagnosis of cleft palate by three-dimensional ultrasound. Ultrasound in medicine & biology 27

2001

Earlier work this paper cites.

Benacerraf, B.R.: Three-dimensional fetal sonography. Journal of Ultrasound in Medicine 21

2002

Earlier work this paper cites.

Prager, R.W., Gee, A.H., Treece, G.M., Cash, C.J., Berman, L.H.: Sensorless freehand 3-d ultrasound using regression of the echo intensity. Ultrasound in medicine & biology 29

2003

Earlier work this paper cites.

Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE transactions on image processing 13

2004

Earlier work this paper cites.

Yoo, J.C., Han, T.H.: Fast normalized cross-correlation. Circuits, systems and signal processing 28

2009

Earlier work this paper cites.

Dückelmann, A.M., Kalache, K.D.: Three-dimensional ultrasound in evaluating the fetus. Prenatal diagnosis 30

2010

Earlier work this paper cites.

Pistorius, L., Stoutenbeek, P., Groenendaal, F., De Vries, L., Manten, G., Mulder, E., Visser, G.: Grade and symmetry of normal fetal cortical development: a longitudinal two-and three-dimensional ultrasound study. Ultrasound in obstetrics & gynecology 36

2010

Earlier work this paper cites.

Kuklisova-Murgasova, M., Quaghebeur, G., Rutherford, M.A., Hajnal, J.V., Schnabel, J.A.: Reconstruction of fetal brain mri with intensity matching and complete outlier removal. Medical image analysis 16

2012

Earlier work this paper cites.

Chen, X., Wen, T., Li, X., Qin, W., Lan, D., Pan, W., Gu, J.: Reconstruction of freehand 3d ultrasound based on kernel regression. Biomedical engineering online 13

2014

Cited alongside, same era.

Papageorghiou, A.T., Ohuma, E.O., Altman, D.G., Todros, T., Ismail, L.C., Lambert, A., Jaffer, Y.A., Bertino, E., Gravett, M.G., Purwar, M.: International standards for fetal growth based on serial ultrasound measurements: the fetal growth longitudinal study of the INTERGROWTH-21st project. The Lancet 384

2014

Cited alongside, same era.

Daoud, M.I., Alshalalfah, A.L., Awwad, F., Al-Najar, M.: Freehand 3d ultrasound imaging system using electromagnetic tracking. In: 2015 International Conference on Open Source Software Computing (OSSCOM). pp. 1–5. IEEE (2015)

2015

Cited alongside, same era.

Gonçalves, L.F.: Three-dimensional ultrasound of the fetus: how does it help? Pediatric radiology 46

2016

Cited alongside, same era.

Moser, F., Huang, R., Papageorghiou, A.T., Papież, B.W., Namburete, A.I.: Automated fetal brain extraction from clinical ultrasound volumes using 3d convolutional neural networks. In: Annual Conference on Medical Image Understanding and Analysis. pp. 151–163. Springer (2019)

2019

Later among the works it cites.

Rahaman, N., Baratin, A., Arpit, D., Draxler, F., Lin, M., Hamprecht, F., Bengio, Y., Courville, A.: On the spectral bias of neural networks. In: International Conference on Machine Learning. pp. 5301–5310. PMLR (2019)

2019

Later among the works it cites.

Sitzmann, V., Zollhöfer, M., Wetzstein, G.: Scene representation networks: Continuous 3d-structure-aware neural scene representations. arXiv preprint arXiv:1906.01618 (2019)

Original

2019

Later among the works it cites.

Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: European Conference on Computer Vision. pp. 405–421. Springer (2020)