VOLUMETRIC MULTIMODALITY NEURAL NETWORK FOR BRAIN TUMOR SEGMENTATION

L.S. CASTILLO, L.A. DAZA, L.C. RIVERA AND P. ARBELÁEZ

13TH INTERNATIONAL CONFERENCE ON MEDICAL INFORMATION PROCESSING AND ANALYSIS (SIPAIM), 2017

Abstract

Brain lesion segmentation is one of the hardest tasks to be solved in computer vision with an emphasis on the medical field. We present a convolutional neural network that produces a semantic segmentation of brain tumors, capable of processing volumetric data along with information from multiple MRI modalities at the same time. This results in the ability to learn from small training datasets and highly imbalanced data. Our method is based on DeepMedic, the state of the art in brain lesion segmentation. We develop a new architecture with more convolutional layers, organized in three parallel pathways with different input resolution, and additional fully connected layers. We tested our method over the 2015 BraTS Challenge dataset, reaching an average dice coefficient of 84%, while the standard DeepMedic implementation reached 74%.

Qualitative results


Figure 1 and 2. Qualitative results.

Method


Figure 3. Proposed Architecture. The kernels of the convolutions in the three pathways are 33 and no padding was made in those operations. The input of the 3 paths are centered in the same voxel, but the medium resolution and low patches are obtained from downsampled versions of the image by factors of 3 and 5, respectively

Results


METHODDICESENSITIVITYSPECIFICITYHAUSDORFF

Deepmedic
Ours
Enh. Wh. Cor.
0.69 0.86 0.68
0.71 0.88 0.68
Enh. Wh. Cor.
0.72 0.86 0.64
0.72 0.86 0.68
Enh. Wh. Cor.
0.99 0.99 0.99
0.99 0.99 0.99
Enh. Wh. Cor.
10.1 25.0 17.5
6.12 9.63 11.4
Table 1.
DATASETDICESENSITIVITYSPECIFICITYHAUSDORFF


Train
Val
Test

Enh. Wh. Cor.
0.74 0.89 0.87
0.71 0.88 0.68
0.65 0.86 0.67
Enh. Wh. Cor.
0.83 0.91 0.89
0.72 0.86 0.68
Enh. Wh. Cor.
0.99 0.99 0.99
0.99 0.99 0.99

Enh. Wh. Cor.
5.85 15.9 11.2
6.12 9.63 11.4
51.7 10.4 36.2
Table 2.

Downloads


Universidad de los Andes | Monitored by Mineducación
Recognition as University: Decree 1297 of May 30th, 1964.
Recognition as legal entity: Resolution 28 of February 23, 1949 Minjusticia.

© Universidad de los Andes. All rights reserved.