J
Johanna Svensson
Researcher at University of Gothenburg
Publications - 19
Citations - 257
Johanna Svensson is an academic researcher from University of Gothenburg. The author has contributed to research in topics: Image quality & Radionuclide therapy. The author has an hindex of 8, co-authored 19 publications receiving 148 citations. Previous affiliations of Johanna Svensson include Sahlgrenska University Hospital.
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Journal ArticleDOI
Nephrotoxicity profiles and threshold dose values for [177Lu]-DOTATATE in nude mice.
TL;DR: Increased serum creatinine and urea values indicated long-term renal toxicity and selective morphological changes in kidney cortex of nude mice were quantified and appeared in a dose dependent manner after injection of high amounts of [(177)Lu]-DOTATATE.
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Comparison of methods for estimation of the intravoxel incoherent motion (IVIM) diffusion coefficient (D) and perfusion fraction (f).
Oscar Jalnefjord,Oscar Jalnefjord,Mats Andersson,Mikael Montelius,Göran Starck,Göran Starck,Anna-Karin Elf,Viktor Johanson,Johanna Svensson,Maria Ljungberg,Maria Ljungberg +10 more
TL;DR: Combined use of D and f improved tumor-to-liver tissue differentiation compared with using D or f separately, and rendered the segmented one preferable due to lower numerical complexity and shorter computational time.
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Bone Marrow Absorbed Doses and Correlations with Hematologic Response During 177Lu-DOTATATE Treatments Are Influenced by Image-Based Dosimetry Method and Presence of Skeletal Metastases
Linn Hagmarker,Johanna Svensson,Tobias Rydén,Martijn van Essen,Anna Sundlöv,Katarina Sjögreen Gleisner,Peter Gjertsson,Peter Bernhardt +7 more
TL;DR: The estimated bone marrow absorbed doses by image-based techniques and the correlation with platelets are influenced by the choice of measured vertebrae and the presence of skeletal metastases.
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Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved 177 Lu images.
Tobias Rydén,Tobias Rydén,J. Heydorn Lagerlöf,J. Hemmingsson,Ida Marin,Johanna Svensson,Magnus Båth,Magnus Båth,Peter Gjertsson,Peter Bernhardt,Peter Bernhardt +10 more
TL;DR: A highly parallel Monte Carlo code for fast, ordered subset expectation maximum (OSEM) reconstructions of SPECT/CT images was developed and reconstructed patient images of 177Lu-DOTATATE treatments revealed clearly improved resolution and contrast.
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Deep-Learning Generation of Synthetic Intermediate Projections Improves 177Lu SPECT Images Reconstructed with Sparsely Acquired Projections.
TL;DR: Adopting SIPs for sparsely acquired projections considerably recovers image quality and could allow a reduced SPECT acquisition time in clinical dosimetry protocols.