Yousef Yeganeh
YOU?
Author Swipe
View article: Unit-Based Histopathology Tissue Segmentation via Multi-Level Feature Representation
Unit-Based Histopathology Tissue Segmentation via Multi-Level Feature Representation Open
We propose UTS, a unit-based tissue segmentation framework for histopathology that classifies each fixed-size 32 * 32 tile, rather than each pixel, as the segmentation unit. This approach reduces annotation effort and improves computationa…
View article: Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis
Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Open
Scaling by training on large datasets has been shown to enhance the quality and fidelity of image generation and manipulation with diffusion models; however, such large datasets are not always accessible in medical imaging due to cost and …
View article: Conformable Convolution for Topologically Aware Learning of Complex Anatomical Structures
Conformable Convolution for Topologically Aware Learning of Complex Anatomical Structures Open
While conventional computer vision emphasizes pixel-level and feature-based objectives, medical image analysis of intricate biological structures necessitates explicit representation of their complex topological properties. Despite their s…
View article: VISAGE: Video Synthesis using Action Graphs for Surgery
VISAGE: Video Synthesis using Action Graphs for Surgery Open
Surgical data science (SDS) is a field that analyzes patient data before, during, and after surgery to improve surgical outcomes and skills. However, surgical data is scarce, heterogeneous, and complex, which limits the applicability of ex…
View article: Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis
Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis Open
Recent advances in generative models for medical imaging have shown promise in representing multiple modalities. However, the variability in modality availability across datasets limits the general applicability of the synthetic data they …
View article: PRISM: Progressive Restoration for Scene Graph-based Image Manipulation
PRISM: Progressive Restoration for Scene Graph-based Image Manipulation Open
Scene graphs have emerged as accurate descriptive priors for image generation and manipulation tasks, however, their complexity and diversity of the shapes and relations of objects in data make it challenging to incorporate them into the m…
View article: AutoPaint: A Self-Inpainting Method for Unsupervised Anomaly Detection
AutoPaint: A Self-Inpainting Method for Unsupervised Anomaly Detection Open
Robust and accurate detection and segmentation of heterogenous tumors appearing in different anatomical organs with supervised methods require large-scale labeled datasets covering all possible types of diseases. Due to the unavailability …
View article: SceneGenie: Scene Graph Guided Diffusion Models for Image Synthesis
SceneGenie: Scene Graph Guided Diffusion Models for Image Synthesis Open
Text-conditioned image generation has made significant progress in recent years with generative adversarial networks and more recently, diffusion models. While diffusion models conditioned on text prompts have produced impressive and high-…
View article: DIAMANT: Dual Image-Attention Map Encoders For Medical Image Segmentation
DIAMANT: Dual Image-Attention Map Encoders For Medical Image Segmentation Open
Although purely transformer-based architectures showed promising performance in many computer vision tasks, many hybrid models consisting of CNN and transformer blocks are introduced to fit more specialized tasks. Nevertheless, despite the…
View article: SCOPE: Structural Continuity Preservation for Medical Image Segmentation
SCOPE: Structural Continuity Preservation for Medical Image Segmentation Open
Although the preservation of shape continuity and physiological anatomy is a natural assumption in the segmentation of medical images, it is often neglected by deep learning methods that mostly aim for the statistical modeling of input dat…
View article: DisPositioNet: Disentangled Pose and Identity in Semantic Image Manipulation
DisPositioNet: Disentangled Pose and Identity in Semantic Image Manipulation Open
Graph representation of objects and their relations in a scene, known as a scene graph, provides a precise and discernible interface to manipulate a scene by modifying the nodes or the edges in the graph. Although existing works have shown…
View article: Shape-Aware Masking for Inpainting in Medical Imaging
Shape-Aware Masking for Inpainting in Medical Imaging Open
Inpainting has recently been proposed as a successful deep learning technique for unsupervised medical image model discovery. The masks used for inpainting are generally independent of the dataset and are not tailored to perform on differe…
View article: Adaptive Personlization in Federated Learning for Highly Non-i.i.d. Data
Adaptive Personlization in Federated Learning for Highly Non-i.i.d. Data Open
Federated learning (FL) is a distributed learning method that offers medical institutes the prospect of collaboration in a global model while preserving the privacy of their patients. Although most medical centers conduct similar medical i…
View article: Y-Net: A Spatiospectral Dual-Encoder Networkfor Medical Image Segmentation
Y-Net: A Spatiospectral Dual-Encoder Networkfor Medical Image Segmentation Open
Automated segmentation of retinal optical coherence tomography (OCT) images has become an important recent direction in machine learning for medical applications. We hypothesize that the anatomic structure of layers and their high-frequenc…