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It’s the great honor that our team’s work in medical image segmentation for Organ at Risk (OAR) for NPC (鼻咽癌) was publicly recognized in the center stage of crowded NVIDIA Taiwan GTC 2018 and presented by CEO/Co-founder Jensen Huang.

The work is reported in Chinese in the NVIDIA Technical Blog — “強大的 GPU 運算效能 大幅提升微小的危急器官標記精準率

We are new to medical image segmentation. However, we did find it hugely important to remove the massive data burdens for the oncologists. Thanks to the luxury resources from NVIDIA and hearty supports from our long-term partner Microsoft Research Asia (MSRA), we are able to contribute for the health of many local friends.

It’s very challenging for segmentation for NPC due to very small organs in the area. For improving the challenging segmentation problem, we aimed to leverage the complementary information between CT and MR images and solved the alignment issue for the two modalities by a GAN-based model. Happy to see the significant improvement from the pilot experiment.

  Tag: nvidia

6 posts
June 9th, 2018

Research in Medical Image Segmentation Highlighted in GTC 2018 Taipei by NVIDIA CEO Huang

It’s the great honor that our team’s work in medical image segmentation for Organ at Risk (OAR) for NPC (鼻咽癌) […]

May 10th, 2017

Quick and incomplete observations from GTC 2017

My quick and incomplete observations  in NVIDIA GTC 2017 keynote. CEO Jen-Hsun Huang had an amazing pitch for the almost two […]

April 4th, 2017

50-min presentation in GTC (GPU Technology Conference) 2017, San Jose

Our GTC (GPU Technology Conference) 2017 scheduled confirmed. 50 min talk scheduled on Monday, May 8, 9:00 AM – 9:50 […]

January 19th, 2017

Our experience with NVIDIA DGX-1, the supercomputer for deep learning

NVIDIA DGX-1的對深度學習效能如何? How effective for DGX-1 with 8 new Tesla P100 GPUs? A few pilot runs. Our training with a […]

January 9th, 2017

The advanced of ADAS (先進駕駛輔助系統的發展)

好奇目前先進駕駛輔助系統(Advanced Driver Assistance Systems;ADAS)領域供應商在深度學習的發展狀況為何。剛好看了一篇關於 Mobileye的報導,又把NVIDIA BB8的技術文章拿來翻了一下,有趣的比對。   Mobileye目前使用的solution是deep learning based 嗎?好奇。 NVIDIA BB8倒是展示了一件事,是不是可以利用end-to-end的作法,讓學習的網路由目前路面影像的輸入直接決定方向盤該轉幾度?這跟之前得先偵測出路面、分割線、道路邊緣的作法大大不同。這也暗示,對於其他深度學習的應用,也可以直接最佳化最後的標的,中間的特徵值或是決策,直接交給網路學習決定。 We do not work on ADAS (advanced […]

September 21st, 2016

Receiving awards for NVIDIA AI Lab (輝達攜手台大成立AI實驗室)

Feel grateful that we are the 5th research lab in the world and 1st in Asia to be sponsored and […]