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Gated Multi-Scale Attention Transformer For Few-Shot Medical Image Segmentation
2024 IEEE International Symposium on Biomedical Imaging (ISBI)
Year: 2024 | Conference Paper |
Few-shot learning has gained a lot of attention in the medical image semantic segmentation field due to the limited availability of annotated medical images. Existing studies use Prototypical Networks (PN) to perform segmentation with a limited number of labeled medical images and have obtained success. However, these approaches overlook pairwise relations between query and support images and the ...Show More
Optimized Neuron Tracing Using Post Hoc Reanalysis
Sara Azzouz;Logan A. Walker;Alexandra Doerner;Kellie L. Geisel;Arianna K. Rodríguez Rivera;Ye Li;Douglas H. Roossien;Dawen Cai
2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)
Year: 2023 | Conference Paper |
Over the last decade, the advances in Brainbow labeling allowed labeling hundreds of neurons with distinct colors in the same field of view of a brain [1], [2]. Reconstruction (or "tracing") of the 3D structures of these images has been enabled by a growing set of software tools for automatic and manual annotation. It is common, however, to have errors introduced by heuristics used by tracing soft...Show More
Cell Instance Segmentation VIA Multi-Scale Non-Local Correlation
2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)
Year: 2023 | Conference Paper |
For cell instance segmentation on Electron Microscopy (EM) images, state-of-the-art methods either conduct pixel-wise classification or follow a detection and segmentation manner. However, both approaches suffer from the enormous cell instances of EM images where cells are tightly close to each other and show inconsistent morphological properties and/or homogeneous appearances. This fact can easil...Show More
MLP-GAN for Brain Vessel Image Segmentation
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
Brain vessel image segmentation can be used as a promising biomarker for better prevention and treatment of different diseases. One successful approach is to consider the segmentation as an image-to-image translation task and perform a conditional Generative Adversarial Network (cGAN) to learn a transformation between two distributions. In this paper, we present a novel multi-view approach, MLP-GA...Show More
Few-shot Medical Image Segmentation with Cycle-resemblance Attention
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Year: 2023 | Conference Paper |
Cited by: Papers (31)
Recently, due to the increasing requirements of medical imaging applications and the professional requirements of annotating medical images, few-shot learning has gained increasing attention in the medical image semantic segmentation field. To perform segmentation with limited number of labeled medical images, most existing studies use Prototypical Networks (PN) and have obtained compelling succes...Show More
Unsupervised Neural Tracing In Densely Labeled Multispectral Brainbow Images
Bin Duan;Logan A Walker;Douglas H Roossien;Fred Y Shen;Dawen Cai;Yan Yan
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
Recent advances in imaging technologies for generating large quantities of high-resolution 3D images, especially multispectral labeling technology such as Brainbow, permits unambiguous differentiation of neighboring neurons in a densely labeled brain. This enables, for the first time, the possibility of studying the connectivity between many neurons from a light microscopy image. The lack of relia...Show More
Sort'N merge: A deterministic microfluidic platform for co-encapsulating distinct particles in microdroplets
2018 IEEE Micro Electro Mechanical Systems (MEMS)
Year: 2018 | Conference Paper |
Cited by: Papers (2)
This paper presents a microfluidic platform for deterministic co-encapsulation of desired combinations of distinct particles in individual droplets. Our microfluidic assay generates droplets co-encapsulating two and three different particles at a yield as high as 87.0% and 80.1%, respectively, by innovative integration of active droplet sorting and downstream merging processes. In conventional app...Show More
Weakly Supervised Actor-Action Segmentation via Robust Multi-task Ranking
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2017 | Conference Paper |
Cited by: Papers (28)
Fine-grained activity understanding in videos has attracted considerable recent attention with a shift from action classification to detailed actor and action understanding that provides compelling results for perceptual needs of cutting-edge autonomous systems. However, current methods for detailed understanding of actor and action have significant limitations: they require large amounts of finel...Show More
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