RESUMEN
Imaging is omnipresent in modern society with imaging devices based on a zoo of physical principles, probing a specimen across different wavelengths, energies and time. Recent years have seen a change in the imaging landscape with more and more imaging devices combining that which previously was used separately. Motivated by these hardware developments, an ever increasing set of mathematical ideas is appearing regarding how data from different imaging modalities or channels can be synergistically combined in the image reconstruction process, exploiting structural and/or functional correlations between the multiple images. Here we review these developments, give pointers to important challenges and provide an outlook as to how the field may develop in the forthcoming years. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.
Asunto(s)
Interpretación de Imagen Asistida por Computador/métodos , Imagen Multimodal/métodos , Algoritmos , Teorema de Bayes , Fenómenos Biofísicos , Diagnóstico por Imagen/métodos , Diagnóstico por Imagen/estadística & datos numéricos , Diagnóstico por Imagen/tendencias , Humanos , Interpretación de Imagen Asistida por Computador/estadística & datos numéricos , Funciones de Verosimilitud , Aprendizaje Automático , Imagen por Resonancia Magnética/métodos , Imagen por Resonancia Magnética/estadística & datos numéricos , Cadenas de Markov , Conceptos Matemáticos , Imagen Multimodal/estadística & datos numéricos , Imagen Multimodal/tendencias , Redes Neurales de la Computación , Tomografía de Emisión de Positrones/métodos , Tomografía de Emisión de Positrones/estadística & datos numéricosRESUMEN
BACKGROUND: Selective internal radiation therapy with Yttrium-90 microspheres is an effective therapy for liver cancer and liver metastases. Yttrium-90 is mainly a high-energy beta particle emitter. These beta particles emit Bremsstrahlung radiation during their interaction with tissue making post-therapy imaging of the radioactivity distribution feasible. Nevertheless, image quality and quantification is difficult due to the continuous energy spectrum which makes resolution modelling, attenuation and scatter estimation challenging and therefore the dosimetry quantification is inaccurate. As a consequence a reconstruction algorithm able to improve resolution could be beneficial. METHODS: In this study, the hybrid kernelised expectation maximisation (HKEM) is used to improve resolution and contrast and reduce noise, in addition a modified HKEM called frozen HKEM (FHKEM) is investigated to further reduce noise. The iterative part of the FHKEM kernel was frozen at the 72nd sub-iteration. When using ordered subsets algorithms the data is divided in smaller subsets and the smallest algorithm iterative step is called sub-iteration. A NEMA phantom with spherical inserts was used for the optimisation and validation of the algorithm, and data from 5 patients treated with Selective internal radiation therapy were used as proof of clinical relevance of the method. RESULTS: The results suggest a maximum improvement of 56% for region of interest mean recovery coefficient at fixed coefficient of variation and better identification of the hot volumes in the NEMA phantom. Similar improvements were achieved with patient data, showing 47% mean value improvement over the gold standard used in hospitals. CONCLUSIONS: Such quantitative improvements could facilitate improved dosimetry calculations with SPECT when treating patients with Selective internal radiation therapy, as well as provide a more visible position of the cancerous lesions in the liver.