7 papers
Zero-shot CT Super-Resolution using Diffusion-based 2D Projection Priors and Signed 3D Gaussians
Jeonghyun Noh, Hyun-Jic Oh, Won-Ki Jeong
Computed tomography (CT) is important in clinical diagnosis, but acquiring high-resolution (HR) CT is constrained by radiation exposure risks. While deep learning-based super-resol…
Synthetic Data Augmentation using Pre-trained Diffusion Models for Long-tailed Food Image Classification
GaYeon Koh, Hyun-Jic Oh, Jeonghyun Noh +1
Deep learning-based food image classification enables precise identification of food categories, further facilitating accurate nutritional analysis. However, real-world food images…
Controllable and Efficient Multi-Class Pathology Nuclei Data Augmentation using Text-Conditioned Diffusion Models
Hyun-Jic Oh, Won-Ki Jeong
In the field of computational pathology, deep learning algorithms have made significant progress in tasks such as nuclei segmentation and classification. However, the potential of…
Co-synthesis of Histopathology Nuclei Image-Label Pairs using a Context-Conditioned Joint Diffusion Model
Seonghui Min, Hyun-Jic Oh, Won-Ki Jeong
In multi-class histopathology nuclei analysis tasks, the lack of training data becomes a main bottleneck for the performance of learning-based methods. To tackle this challenge, pr…
Evaluation and improvement of Segment Anything Model for interactive histopathology image segmentation
SeungKyu Kim, Hyun-Jic Oh, Seonghui Min +1
With the emergence of the Segment Anything Model (SAM) as a foundational model for image segmentation, its application has been extensively studied across various domains, includin…
Scribble-supervised Cell Segmentation Using Multiscale Contrastive Regularization
Hyun-Jic Oh, Kanggeun Lee, Won-Ki Jeong
Current state-of-the-art supervised deep learning-based segmentation approaches have demonstrated superior performance in medical image segmentation tasks. However, such supervised…
DiffMix: Diffusion Model-based Data Synthesis for Nuclei Segmentation and Classification in Imbalanced Pathology Image Datasets
Hyun-Jic Oh, Won-Ki Jeong
Nuclei segmentation and classification is a significant process in pathology image analysis. Deep learning-based approaches have greatly contributed to the higher accuracy of this…