Attributing Uncertainties in the Identification of Hotspots in SPECT Imaging

TL;DR

This paper introduces a new framework for quantifying uncertainties in hotspot detection in SPECT imaging, enhancing confidence in lesion identification through simulation-based analysis.

Contribution

The paper presents a novel method that attributes quantifiable uncertainties to hotspot detection in SPECT images using the RISE reconstruction approach.

Findings

Successfully applied to GATE phantom simulation data

Provides confidence levels for hotspot parameters

Enhances reliability of SPECT lesion detection

Abstract

In SPECT imaging, the identification and detection of a lesion rely either on visual inspection of the reconstructed tomographic images or post-processing image analysis methods. Both approaches do not provide the capability to attribute a quantifiable uncertainty to this identification. We present a framework which allows the quantification of this uncertainty and the assignment of a level of confidence to the detection of hotspots. Based on the "Reconstructed Image from Simulations Ensemble" (RISE), an image reconstruction method, the presented scheme uses the set of projection measurements to derive the parameters defining the uptake of radioactivity, the position and the size of a hotspot, and as well as their associated uncertainties. The capabilities of the proposed method are demonstrated with projection data from GATE phantom simulations.