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eess.IV2025
ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging
Eichi Takaya, Ryusei Inamori
Background and objective: Expert annotations limit large-scale supervised pretraining in medical imaging, while ubiquitous metadata (modality, anatomical region) remain underused.…
eess.IV2024
In-context learning for medical image segmentation
Eichi Takaya, Shinnosuke Yamamoto
Annotation of medical images, such as MRI and CT scans, is crucial for evaluating treatment efficacy and planning radiotherapy. However, the extensive workload of medical professio…
eess.IV2023
PlaNet-S: Automatic Semantic Segmentation of Placenta
Shinnosuke Yamamoto, Isso Saito, Eichi Takaya +5
[Purpose] To develop a fully automated semantic placenta segmentation model that integrates the U-Net and SegNeXt architectures through ensemble learning. [Methods] A total of 218…