Deep Learning-Based Image Reconstruction for Different Medical Imaging Modalities

Table 1

Medical image reconstruction techniques.

Methodologies applied	Performance	Drawbacks
Analytical methods	They are efficient.	Requires proper sampling.
Iterative methods	The imaging device’s statistical and physical features are considered.	Inhomogeneous magnetic fields, for example, cause differences between the model and physical variables.
Learning-based and data-driven methods	Learned signal models can be used to rebuild images from low-quality data.	They are inefficient in terms of computing and necessitate enormous amounts of training data.