Back to Search
Start Over
Semantic Segmentation of Colon Glands in Inflammatory Bowel Disease Biopsies
- Source :
- Advances in Intelligent Systems and Computing ISBN: 9783319912103, ITIB
- Publication Year :
- 2018
- Publisher :
- Springer International Publishing, 2018.
-
Abstract
- Robust delineation of tissue components in hematoxylin and eosin (H&E) stained slides is a critical step in quantifying tissue morphology. Fully convolutional neural networks (FCN) are ideally suited for automatic and efficient segmentation of tissue components in H&E slides. However, their performance relies on the network architecture, quality and depth of training. Here we introduce a set of 802 image tiles of colon biopsies from 2 subjects with inflammatory bowel disease (IBD) annotated for glandular epithelium (EP), gland lumen together with goblet cells (LG), and stroma (ST). We either trained the FCN-8s de-novo on our images (DN-FCN-8s) or pre-trained on the ImageNet dataset and fine-tuned on our images (FT-FCN-8s). For comparison, we used the U-Net trained de-novo. The training involved 700/802 images, leaving 102 images as a testing set. Ultimately, each model was validated in an independent digital biopsy slide. We also determined how the number of images used for training affects the performance of the model and observed a plateau in trainability at 700 images. In the testing set, U-Net and FT-FCN-8s achieved accuracies of 92.30% and 92.26% respectively. In the independent biopsy slide, U-Net demonstrated a segmentation accuracy of 88.64%, with F1-scores of 0.74 (EP), 0.92 (LG), and 0.93 (ST). The performance of the FT-FCN-8s was slightly worse, but the model required fewer images to reach a high classification performance. Our data demonstrate that all 3 FCNs are appropriate for segmentation of glands in biopsies from patients with IBD and open the door for quantification of IBD associated pathologies.
- Subjects :
- 0301 basic medicine
medicine.medical_specialty
medicine.diagnostic_test
business.industry
Deep learning
H&E stain
Lumen (anatomy)
medicine.disease
Convolutional neural network
Inflammatory bowel disease
03 medical and health sciences
Glandular epithelium
030104 developmental biology
0302 clinical medicine
030220 oncology & carcinogenesis
Biopsy
medicine
Segmentation
Radiology
Artificial intelligence
business
Subjects
Details
- ISBN :
- 978-3-319-91210-3
- ISBNs :
- 9783319912103
- Database :
- OpenAIRE
- Journal :
- Advances in Intelligent Systems and Computing ISBN: 9783319912103, ITIB
- Accession number :
- edsair.doi...........ba28b7949f1950b15ff3508ee4262639