Medical Image Segmentation Papers

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Medical Image Segmentation Review: The success of U …

https://arxiv.org/abs/2211.14830

U-Net is the most widespread image segmentation architecture due to its flexibility, optimized modular design, and success in all medical image modalities. Over …

Efficient Medical Image Segmentation Based on …

https://arxiv.org/abs/2108.09987

Recent advances have been made in applying convolutional neural networks to achieve more precise prediction results for medical image segmentation problems. …

Medical Image Segmentation | Papers With …

https://paperswithcode.com/task/medical-image-segmentation

Liver Segmentation; Semi-supervised Medical …

Medical image segmentation using deep learning: A survey

https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/ipr2.12419

Popular medical image segmentation tasks include liver and liver-tumour segmentation , brain and brain-tumour segmentation , optic disc segmentation , cell segmentation , …

Segmentation technique for medical image processing: A …

https://ieeexplore.ieee.org/document/8365301

Segmentation is one of the popular and efficient technique in context to medical image analysis. The purpose of the segmentation is to clearly extract the …

Medical image recognition and segmentation of …

https://pubmed.ncbi.nlm.nih.gov/34130088/

Objective: In order to improve the efficiency of gastric cancer pathological slice image recognition and segmentation of cancerous regions, this paper proposes an automatic …

Generative adversarial networks in medical image …

https://pubmed.ncbi.nlm.nih.gov/34864584/

This paper introduces the origin, working principle, and extended variant of GAN, and it reviews the latest development of GAN-based medical image segmentation methods. …

Towards Cross-Modality Medical Image Segmentation …

https://aaai.org/papers/00775-towards-cross-modality-medical-image-segmentation-with-online-mutual-knowledge-distillation/

To alleviate the learning difficulties caused by modality-specific appearance discrepancy, we first present an Image Alignment Module (IAM) to narrow the appearance gap between …

Label-Efficient Hybrid-Supervised Learning for Medical …

https://aaai.org/papers/02026-label-efficient-hybrid-supervised-learning-for-medical-image-segmentation/

Due to the lack of expertise for medical image annotation, the investigation of label-efficient methodology for medical image segmentation becomes a heated topic. Recent …

A Review of Deep-Learning-Based Medical …

https://www.mdpi.com/2071-1050/13/3/1224

As an emerging biomedical image processing technology, medical image segmentation has made great contributions to sustainable medical care. Now it has …

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