Intracranial aneurysm detection: an object detection perspective - INRIA 2 Accéder directement au contenu
Article Dans Une Revue International Journal of Computer Assisted Radiology and Surgery Année : 2024

Intracranial aneurysm detection: an object detection perspective

Résumé

Intracranial aneurysm detection from 3D Time-Of-Flight Magnetic Resonance Angiography images is a problem of increasing clinical importance. Recently, a streak of methods have shown promising performance by using segmentation neural networks. However, these methods may be less relevant in a clinical settings where diagnostic decisions rely on detecting objects rather than their segmentation. We introduce a 3D single-stage object detection method tailored for small object detection such as aneurysms. Our anchor-free method incorporates fast data annotation, adapted data sampling and generation to address class imbalance problem, and spherical representations for improved detection. A comprehensive evaluation was conducted, comparing our method with the state-of-the-art SCPM-Net, nnDetection and nnUNet baselines, using two datasets comprising 402 subjects. The evaluation used adapted object detection metrics. Our method exhibited comparable or superior performance, with an average precision of 78.96%, sensitivity of 86.78%, and 0.53 false positives per case. Our method significantly reduces the detection complexity compared to existing methods and highlights the advantages of object detection over segmentation-based approaches for aneurysm detection. It also holds potential for application to other small object detection problems.
Fichier sous embargo
Fichier sous embargo
0 5 13
Année Mois Jours
Avant la publication
jeudi 17 octobre 2024
Fichier sous embargo
jeudi 17 octobre 2024
Connectez-vous pour demander l'accès au fichier

Dates et versions

hal-04557555 , version 1 (24-04-2024)

Licence

Paternité

Identifiants

Citer

Youssef Assis, Liang Liao, Fabien Pierre, René Anxionnat, Erwan Kerrien. Intracranial aneurysm detection: an object detection perspective. International Journal of Computer Assisted Radiology and Surgery, 2024, ⟨10.1007/s11548-024-03132-z⟩. ⟨hal-04557555⟩
0 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More