Search Results for author: Sai Mu Dalike Abaxi

Found 2 papers, 1 papers with code

Deep Learning Approach for Large-Scale, Real-Time Quantification of Green Fluorescent Protein-Labeled Biological Samples in Microreactors

no code implementations4 Sep 2023 Yuanyuan Wei, Sai Mu Dalike Abaxi, Nawaz Mehmood, Luoquan Li, Fuyang Qu, Guangyao Cheng, Dehua Hu, Yi-Ping Ho, Scott Wu Yuan, Ho-Pui Ho

Absolute quantification of biological samples entails determining expression levels in precise numerical copies, offering enhanced accuracy and superior performance for rare templates.

Transfer Learning

Generalist Vision Foundation Models for Medical Imaging: A Case Study of Segment Anything Model on Zero-Shot Medical Segmentation

1 code implementation25 Apr 2023 Peilun Shi, Jianing Qiu, Sai Mu Dalike Abaxi, Hao Wei, Frank P. -W. Lo, Wu Yuan

In this paper, we examine the recent Segment Anything Model (SAM) on medical images, and report both quantitative and qualitative zero-shot segmentation results on nine medical image segmentation benchmarks, covering various imaging modalities, such as optical coherence tomography (OCT), magnetic resonance imaging (MRI), and computed tomography (CT), as well as different applications including dermatology, ophthalmology, and radiology.

Computed Tomography (CT) Image Segmentation +4

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