Improved MRA Synthesis with KAN-based Network with Global MIP Guidance

Motivation: Time-of-Flight (TOF) Magnetic Resonance Angiography (MRA) is critical for diagnosing vascular diseases such as aneurysms, but long acquisition time and noise susceptibility limit its clinical efficiency. Goal(s): To avoid the long scan time, we aim to synthesize high-quality TOF-MRA images using faster T1-weighted (T1w) and T2-weighted (T2w) sequences. Approach: We propose a 2.5D Kolmogorov-Arnold Networks (KAN)-based model, termed sKAN, which integrates KAN with snake convolution. Results: The Synthesized MRA (Syn-MRA) images closely resemble standard-of-care (SOC) MRA, displaying realistic vessel textures and reduced noise. They can serve as a potential alternative to SOC-TOF-MRA, reducing the need for prolonged scan time. Impact: The proposed method enables TOF-MRA synthesis from faster T1- and T2-weighted MRI images. The synthesized images closely match standard-of-care (SOC) TOF-MRA, accurately depicting vessels in major central areas, thus eliminating need for lengthy acquisition process of SOC-TOF-MRA in clinical settings.