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On the Cover: Hepatocellular Cancer Treatment

The interdisciplinary WAW-TACE dataset includes 233 cancer patients treated with transarterial chemotherapy (Bartnik et al). See commentary by Bitar and Chapiro.

Detecting Cervical Spine Fractures

How well do top models from the RSNA 2022 Cervical Spine Fracture Detection competition perform on real-world trauma cases? (Hu and Patel et al). See commentary by Levi and Politi.

The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset

The RATIC dataset is the largest publicly available dataset of annotated abdominal CT studies related to traumatic injuries (Rudie et al).

Data Augmentation Framework with Synthetic Patient Image Data

Data augmentation with synthetic patient data substantially improved performance of AI models on unseen MRI data (Brugnara and Jayachandran Preetha et al).

Localization of Intracranial Hemorrhage on CT Scans

A weakly supervised deep learning model predicted and localized intracranial hemorrhage at the image level (Wu et al). Commentary by Akinci D’Antonoli and Rudie.

Deep Learning for Interpretable Brain MRI Lesion Detection

ReportGuidedNet, developed with radiology reports, outperformed PlainNet in diagnosing 14 brain diseases and normal brain on MRI scans (Dai et al).

Fetal Brain MR Image Segmentation

Optimized Swin-UNETR model showed comparable performance versus state-of-the-art models in resting-state fMRI fetal brain segmentation (Pecco et al).