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Found 7 papers, 3 papers with code
Frame by Familiar Frame: Understanding Replication in Video Diffusion Models
In our paper, we present a systematic investigation into the phenomenon of sample replication in video diffusion models.
Ambiguous Medical Image Segmentation using Diffusion Models
Collective insights from a group of experts have always proven to outperform an individual's best diagnostic for clinical tasks.
Simultaneous Bone and Shadow Segmentation Network using Task Correspondence Consistency
Segmenting both bone surface and the corresponding acoustic shadow are fundamental tasks in ultrasound (US) guided orthopedic procedures.
Orientation-guided Graph Convolutional Network for Bone Surface Segmentation
Due to imaging artifacts and low signal-to-noise ratio in ultrasound images, automatic bone surface segmentation networks often produce fragmented predictions that can hinder the success of ultrasound-guided computer-assisted surgical procedures.
ViPTT-Net: Video pretraining of spatio-temporal model for tuberculosis type classification from chest CT scans
We explore the idea of whether pretraining a model on realistic videos could improve performance rather than training the model from scratch, intended for tuberculosis type classification from chest CT scans.
Uniformizing Techniques to Process CT scans with 3D CNNs for Tuberculosis Prediction
A common approach to medical image analysis on volumetric data uses deep 2D convolutional neural networks (CNNs).
Improving Malaria Parasite Detection from Red Blood Cell using Deep Convolutional Neural Networks
The evaluation metric accuracy and loss along with 5-fold cross validation was used to compare and select the best performing architecture.
