Purpose Predicting the consistency of benign central nervous system (CNS) tumors prior to
surgery helps to improve surgical outcomes. This review summarizes and analyzes the …

Rationale and Objectives Ki67 proliferation index is associated with more aggressive tumor
behavior and recurrence of pituitary adenomas (PAs). Recently, radiomics and deep …

Objective To evaluate the diagnostic performance and image quality of 1.5-mm slice
thickness MRI with deep learning-based image reconstruction (1.5-mm MRI+ DLR) …

Purpose: Brain MRI with high spatial resolution allows for a more detailed delineation of
multiple sclerosis (MS) lesions. The recently developed deep learning-based reconstruction …

In veterinary practice, thin‐sliced thoracolumbar MRI is useful in detecting small lesions,
especially in small‐breed dogs. However, it is challenging due to the partial volume …

Purpose With the slice thickness routinely used in elbow MRI, small or subtle lesions may be
overlooked or misinterpreted as insignificant. To compare 1 mm slice thickness MRI (1 mm …

Background Accelerated magnetic resonance imaging sequences reconstructed using the
vendor-provided Recon deep learning algorithm (DL-MRI) were found to be more likely than …

Purpose To evaluate the diagnostic value of T1-weighted 3D fast spin-echo sequence
(CUBE) with deep learning-based reconstruction (DLR) for depiction of pituitary adenoma …

Optimal magnetic resonance imaging (MRI) quality and shorter scan time are challenging to
achieve in veterinary practices. Recently, deep learning‐based reconstruction (DLR) has …