TY - GEN

T1 - Local Gamma Augmentation for Ischemic Stroke Lesion Segmentation on MRI

AU - Middleton, Jon

AU - Bauer, Marko

AU - Johansen, Jacob

AU - Perslev, Mathias

AU - Sheng, Kaining

AU - Ingala, Silvia

AU - Nielsen, Mads

AU - Pai, Akshay

N1 - Publisher Copyright: © NLDL 2024. All rights reserved.

PY - 2024

Y1 - 2024

N2 - The identification and localisation of pathological tissues in medical images continues to command much attention among deep learning practitioners. When trained on abundant datasets, deep neural networks can match or exceed human performance. However, the scarcity of annotated data complicates the training of these models. Data augmentation techniques can compensate for a lack of training samples. However, many commonly used augmentation methods can fail to provide meaningful samples during model fitting. We present local gamma augmentation, a technique for introducing new instances of intensities in pathological tissues. We leverage local gamma augmentation to compensate for a bias in intensities corresponding to ischemic stroke lesions in human brain MRIs. On three datasets, we show how local gamma augmentation can improve the image-level sensitivity of a deep neural network tasked with ischemic stroke lesion segmentation on magnetic resonance images.

AB - The identification and localisation of pathological tissues in medical images continues to command much attention among deep learning practitioners. When trained on abundant datasets, deep neural networks can match or exceed human performance. However, the scarcity of annotated data complicates the training of these models. Data augmentation techniques can compensate for a lack of training samples. However, many commonly used augmentation methods can fail to provide meaningful samples during model fitting. We present local gamma augmentation, a technique for introducing new instances of intensities in pathological tissues. We leverage local gamma augmentation to compensate for a bias in intensities corresponding to ischemic stroke lesions in human brain MRIs. On three datasets, we show how local gamma augmentation can improve the image-level sensitivity of a deep neural network tasked with ischemic stroke lesion segmentation on magnetic resonance images.

M3 - Article in proceedings

AN - SCOPUS:85189352715

T3 - Proceedings of Machine Learning Research

SP - 158

EP - 164

BT - Proceedings of the 5th Northern Lights Deep Learning Conference ({NLDL})

PB - PMLR

T2 - 5th Northern Lights Deep Learning Conference, NLDL 2024

Y2 - 9 January 2024 through 11 January 2024

ER -