4D-PET reconstruction of dynamic non-small cell lung cancer [18-F]-FMISO-PET data using adaptive-knot cubic b-splines
4D-PET reconstruction has the potential to significantly increase the signal-to-noise ratio in dynamic PET by fitting smooth temporal functions during the reconstruction. However, the optimal choice of temporal function remains an open question. A 4D-PET reconstruction algorithm using adaptive-knot...
| Príomhchruthaitheoirí: | , , , , , |
|---|---|
| Formáid: | Conference item |
| Foilsithe / Cruthaithe: |
Institute of Electrical and Electronics Engineers
2017
|
| _version_ | 1826284931750297600 |
|---|---|
| author | Ralli, G McGowan, D Chappell, M Sharma, R Higgins, G Fenwick, J |
| author_facet | Ralli, G McGowan, D Chappell, M Sharma, R Higgins, G Fenwick, J |
| author_sort | Ralli, G |
| collection | OXFORD |
| description | 4D-PET reconstruction has the potential to significantly increase the signal-to-noise ratio in dynamic PET by fitting smooth temporal functions during the reconstruction. However, the optimal choice of temporal function remains an open question. A 4D-PET reconstruction algorithm using adaptive-knot cubic B-splines is proposed. Using realistic Monte-Carlo simulated data from a digital patient phantom representing an [18-F]-FMISO-PET scan of a non-small cell lung cancer patient, this method was compared to a spectral model based 4D-PET reconstruction and the conventional MLEM and MAP algorithms. Within the entire patient region the proposed algorithm produced the best bias-noise trade-off, while within the tumor region the spline- and spectral model-based reconstructions gave comparable results. |
| first_indexed | 2024-03-07T01:21:15Z |
| format | Conference item |
| id | oxford-uuid:906d68a6-2bc0-4bc7-b62c-73dfa3c1f8f8 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T01:21:15Z |
| publishDate | 2017 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | oxford-uuid:906d68a6-2bc0-4bc7-b62c-73dfa3c1f8f82022-03-26T23:11:29Z4D-PET reconstruction of dynamic non-small cell lung cancer [18-F]-FMISO-PET data using adaptive-knot cubic b-splinesConference itemhttp://purl.org/coar/resource_type/c_5794uuid:906d68a6-2bc0-4bc7-b62c-73dfa3c1f8f8Symplectic Elements at OxfordInstitute of Electrical and Electronics Engineers2017Ralli, GMcGowan, DChappell, MSharma, RHiggins, GFenwick, J4D-PET reconstruction has the potential to significantly increase the signal-to-noise ratio in dynamic PET by fitting smooth temporal functions during the reconstruction. However, the optimal choice of temporal function remains an open question. A 4D-PET reconstruction algorithm using adaptive-knot cubic B-splines is proposed. Using realistic Monte-Carlo simulated data from a digital patient phantom representing an [18-F]-FMISO-PET scan of a non-small cell lung cancer patient, this method was compared to a spectral model based 4D-PET reconstruction and the conventional MLEM and MAP algorithms. Within the entire patient region the proposed algorithm produced the best bias-noise trade-off, while within the tumor region the spline- and spectral model-based reconstructions gave comparable results. |
| spellingShingle | Ralli, G McGowan, D Chappell, M Sharma, R Higgins, G Fenwick, J 4D-PET reconstruction of dynamic non-small cell lung cancer [18-F]-FMISO-PET data using adaptive-knot cubic b-splines |
| title | 4D-PET reconstruction of dynamic non-small cell lung cancer [18-F]-FMISO-PET data using adaptive-knot cubic b-splines |
| title_full | 4D-PET reconstruction of dynamic non-small cell lung cancer [18-F]-FMISO-PET data using adaptive-knot cubic b-splines |
| title_fullStr | 4D-PET reconstruction of dynamic non-small cell lung cancer [18-F]-FMISO-PET data using adaptive-knot cubic b-splines |
| title_full_unstemmed | 4D-PET reconstruction of dynamic non-small cell lung cancer [18-F]-FMISO-PET data using adaptive-knot cubic b-splines |
| title_short | 4D-PET reconstruction of dynamic non-small cell lung cancer [18-F]-FMISO-PET data using adaptive-knot cubic b-splines |
| title_sort | 4d pet reconstruction of dynamic non small cell lung cancer 18 f fmiso pet data using adaptive knot cubic b splines |
| work_keys_str_mv | AT rallig 4dpetreconstructionofdynamicnonsmallcelllungcancer18ffmisopetdatausingadaptiveknotcubicbsplines AT mcgowand 4dpetreconstructionofdynamicnonsmallcelllungcancer18ffmisopetdatausingadaptiveknotcubicbsplines AT chappellm 4dpetreconstructionofdynamicnonsmallcelllungcancer18ffmisopetdatausingadaptiveknotcubicbsplines AT sharmar 4dpetreconstructionofdynamicnonsmallcelllungcancer18ffmisopetdatausingadaptiveknotcubicbsplines AT higginsg 4dpetreconstructionofdynamicnonsmallcelllungcancer18ffmisopetdatausingadaptiveknotcubicbsplines AT fenwickj 4dpetreconstructionofdynamicnonsmallcelllungcancer18ffmisopetdatausingadaptiveknotcubicbsplines |