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Found 10 papers, 3 papers with code
ProMISe: Promptable Medical Image Segmentation using SAM
Our experiments demonstrate that such adaptive prompts significantly improve SAM's non-fine-tuned performance in MIS.
Ranked #1 on
Medical Image Segmentation
on ISIC 2018
Atrial Septal Defect Detection in Children Based on Ultrasound Video Using Multiple Instances Learning
In addition, data from 30 children patients (15 positives and 15 negatives) are collected for clinician testing and compared to our model test results (these 30 samples do not participate in model training).
Distortion-Disentangled Contrastive Learning
The POCL method typically uses a single loss function to extract the distortion invariant representation (DIR) which describes the proximity of positive-pair representations affected by different distortions.
DualStreamFoveaNet: A Dual Stream Fusion Architecture with Anatomical Awareness for Robust Fovea Localization
Accurate fovea localization is essential for analyzing retinal diseases to prevent irreversible vision loss.
DuAT: Dual-Aggregation Transformer Network for Medical Image Segmentation
The GLSA has the ability to aggregate and represent both global and local spatial features, which are beneficial for locating large and small objects, respectively.
Ranked #1 on
Medical Image Segmentation
on 2018 Data Science Bowl
Stepwise Feature Fusion: Local Guides Global
However, due to the structure of polyps image and the varying shapes of polyps, it easy for existing deep learning models to overfitting the current dataset.
Ranked #2 on
Medical Image Segmentation
on 2018 Data Science Bowl
A Robust Framework of Chromosome Straightening with ViT-Patch GAN
The generator learns the motion representation of chromosomes for straightening.
Enhancing Population Persistence by a Protection Zone in a Reaction-Diffusion Model with Strong Allee Effect
Protecting endangered species has been an important issue in ecology.
Dynamical Systems
Autoencoder Based Residual Deep Networks for Robust Regression Prediction and Spatiotemporal Estimation
To have a superior generalization, a deep learning neural network often involves a large size of training sample.
