2 papers
cs.CV2026
Meta-D: Metadata-Aware Architectures for Brain Tumor Analysis and Missing-Modality Segmentation
SangHyuk Kim, Daniel Haehn, Sumientra Rampersad
We present Meta-D, an architecture that explicitly leverages categorical scanner metadata such as MRI sequence and plane orientation to guide feature extraction for brain tumor ana…
cs.CV2025
Designing a Convolutional Neural Network for High-Accuracy Oral Cavity Squamous Cell Carcinoma (OCSCC) Detection
Vishal Manikanden, Aniketh Bandlamudi, Daniel Haehn
Oral Cavity Squamous Cell Carcinoma (OCSCC) is the most common type of head and neck cancer. Due to the subtle nature of its early stages, deep and hidden areas of development, and…