Hello, I'm Anh Tien Nguyen

I am a second-year Master’s student in Electrical Engineering at Korea University, supervised by Prof. Jin Tae Kwak. My works focus on applying deep learning to medical imaging, especially computational pathology. Recently, I am working on multiple instance learning (MIL) for whole slide images. Email: ngtienanh (at) korea (dot) ac (dot) kr

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News

  • May 2024: TQx has been accepted at MICCAI 2024 (Early accept, top 11%).
  • Sep 2023: GPC has been accepted to MICCAI-MedAGI 2023 with “Best Paper Honorable Mention”.

Publications

Towards a text-based quantitative and explainable histopathology image analysis

Towards a text-based quantitative and explainable histopathology image analysis

Anh Tien Nguyen*, Trinh Thi Le Vuong, Jin Tae Kwak
MICCAI 2024 (Early accept, top 11%)

An explainable method to utilize texts for quantifying pathology images

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CAMP: Continuous and Adaptive Learning Model in Pathology

CAMP: Continuous and Adaptive Learning Model in Pathology

Anh Tien Nguyen*, Keunho Byeon, Kyungeun Kim, Boram Song, Seoung Wan, Jin Tae Kwak
Under review (journal)

A framework for continuous learning that is applicable for any vision model.

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GPC: Generative and General Pathology Image Classifier

GPC: Generative and General Pathology Image Classifier

Anh Tien Nguyen*, Jin Tae Kwak
MICCAI-MedAGI 2023 (Best Paper Honorable Mention)

A task-agnostic generative and general pathology image classifier

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