Though DL-based image reconstruction methods are gaining popularity in the field, evidence suggests that they may be unstable, meaning small changes to collected measurements could cause large differences in the resulting image. These challenges are exacerbated when image sampling is incomplete (in other words, when fewer raw imaging measurements are collected to reduce time and costs).
“Although DL has been shown to be useful in many contexts, there’s a lot going on inside these methods that are … still viewed as a black box by many researchers,” Bhadra said. “That makes it hard to tell when a medical abnormality might actually be a false structure created by the machine-learning method. The novelty of our work is in mathematically defining those false structures, which we call hallucinations.”
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Kelkar, Bhadra, and colleagues provide a formal definition of hallucinations based on fundamental principles of imaging science. Through numerical studies, they evaluated the presence and impact of hallucinations across both DL-based and non-data-driven reconstruction methods. These methods were used to reconstruct images of adult and pediatric brain tissue — with the DL-based method trained only on adult brain images — and evaluate the effect of bias from the training images.
“Our goal in mathematically defining hallucinations was to separate sources of systemic error, like measurement errors or noise, from errors that arise due to inaccurate assumptions about the to-be-imaged subject that are built into the image reconstruction method,” Kelkar said.
The impact of a generated hallucination is highly dependent on the type of tissue being imaged and the disease being monitored. Sophisticated image processing methods can be applied to identify how a particular diagnostic task may be affected by the presence of hallucinations.
“A hallucination could be something minor, such as a slight imperfection at the boundary of a tissue, or it could be something major, like introducing an entire fold of tissue in the brain,” Kelkar said.
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