Pyramid-Focus-Augmentation: Medical Image Segmentation with Step-Wise Focus
Segmentation of findings in the gastrointestinal tract is a challenging but also an important task which is an important building stone for sufficient automatic decision support systems. In this work, we present our solution for the Medico 2020 task, which focused on the problem of colon polyp segmentation. We present our simple but efficient idea of using an augmentation method that uses grids in a pyramid-like manner (large to small) for segmentation. Our results show that the proposed methods work as indented and can also lead to comparable results when competing with other methods.
Code (1)
Tasks
Image SegmentationMedical Image SegmentationSegmentationSemantic SegmentationSimilar Papers 제목 키워드 기반
J-CaPA : Joint Channel and Pyramid Attention Improves Medical Image Segmentation
Medical image segmentation is crucial for diagnosis and treatment planning. Traditional CNN-based models, like U-Net, have shown promising results but struggle to capture long-range dependencies and global context. To ad…
Data AugmentationImage SegmentationMedical Image SegmentationOrgan Segmentation+2DeepPyramid+: Medical Image Segmentation using Pyramid View Fusion and Deformable Pyramid Reception
Semantic Segmentation plays a pivotal role in many applications related to medical image and video analysis. However, designing a neural network architecture for medical image and surgical video segmentation is challengi…
Image SegmentationMedical Image SegmentationSegmentationSemantic Segmentation+2CANet: Context aware network with dual-stream pyramid for medical image segmentation
Owing to the various object types and scales, complicated backgrounds, and similar appearance between tissues in medical images, it is difficult to extract some valuable information from different medical images. In this…
2D Semantic SegmentationDecoderImage SegmentationMedical Image Segmentation+3Pyramid Medical Transformer for Medical Image Segmentation
Deep neural networks have been a prevailing technique in the field of medical image processing. However, the most popular convolutional neural networks (CNNs) based methods for medical image segmentation are imperfect be…
Image SegmentationMedical Image SegmentationSegmentationSemantic SegmentationLesionMix: A Lesion-Level Data Augmentation Method for Medical Image Segmentation
Data augmentation has become a de facto component of deep learning-based medical image segmentation methods. Most data augmentation techniques used in medical imaging focus on spatial and intensity transformations to imp…
Data AugmentationDiversityImage SegmentationMedical Image Segmentation+2