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Found 8 papers, 4 papers with code
PSFHS Challenge Report: Pubic Symphysis and Fetal Head Segmentation from Intrapartum Ultrasound Images
This challenge aimed to enhance the development of automatic segmentation algorithms at an international scale, providing the largest dataset to date with 5, 101 intrapartum ultrasound images collected from two ultrasound machines across three hospitals from two institutions.
Segmenting Fetal Head with Efficient Fine-tuning Strategies in Low-resource Settings: an empirical study with U-Net
Among these models, U-Net has become a standard approach for accurate segmentation.
Generative Diffusion Model Bootstraps Zero-shot Classification of Fetal Ultrasound Images In Underrepresented African Populations
It demonstrates that the FU-LoRA method is effective in the zero-shot classification of fetal ultrasound images in low-resource settings.
Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for Zero shot Medical Image Segmentation
To adapt SAM to medical imaging, existing methods primarily rely on tuning strategies that require extensive data or prior prompts tailored to the specific task, making it particularly challenging when only a limited number of data samples are available.
P-Mamba: Marrying Perona Malik Diffusion with Mamba for Efficient Pediatric Echocardiographic Left Ventricular Segmentation
Specifically, we utilize the recently proposed ViM layers from the vision mamba to enhance our model's computational and memory efficiency while modeling global dependencies. In the DWT-based Perona-Malik Diffusion (PMD) Block, we devise a PMD Block for noise suppression while preserving the left ventricle's local shape cues.
MiTU-Net: A fine-tuned U-Net with SegFormer backbone for segmenting pubic symphysis-fetal head
The MiTU-Net model is based on an encoder-decoder framework, utilizing a pre-trained efficient transformer to enhance feature representation.
Lightweight Framework for Automated Kidney Stone Detection using coronal CT images
In this paper, we propose a lightweight fusion framework for kidney detection and kidney stone diagnosis on coronal CT images.
Evaluate Fine-tuning Strategies for Fetal Head Ultrasound Image Segmentation with U-Net
This method addresses the challenges associated with training a CNN network from scratch.
