mshunshin / SegNetCMR

A Tensorflow implementation of SegNet for cardiac MRI segmentation
MIT License
74 stars 35 forks source link

About Paper #6

Open dangleee opened 5 years ago

dangleee commented 5 years ago

Whether this model has been published in relevant literature, I hope to see some detailed descriptions of the network in the literature,thanks

mshunshin commented 5 years ago

It is based on the one here http://mi.eng.cam.ac.uk/projects/segnet/

On 9 Jan 2019, at 03:30, dangleee notifications@github.com wrote:

Whether this model has been published in relevant literature, I hope to see some detailed descriptions of the network in the literature,thanks

— You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub, or mute the thread.

dangleee commented 5 years ago

Thanks for your e-mail. Is your training model in CMR images the same as the SegNet in CamVid dataset of this paper(A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation)? Otherwise, I want to know the proformance of your training model in CMR images, so, I try to train the CMR image, but a error is showed. I believe it is the problem of encoder, but I add the code of # -- coding: utf-8 -- in the start of model. I hope to get your help. Thanks.

党 豪 Dang Hao 北京邮电大学自动化学院 Automation school of BUPT 地址:北京市海淀区西土城路10号北京邮电大学新科研楼808室
Beijing University of Posts and Telecommunications No.10 Xitucheng Road, Haidian District, Beijing, China

电话:17801157739/15136230566

From: Matthew Shun-Shin Date: 2019-01-09 23:55 To: mshunshin/SegNetCMR CC: dangleee; Author Subject: Re: [mshunshin/SegNetCMR] About Paper (#6) It is based on the one here http://mi.eng.cam.ac.uk/projects/segnet/

On 9 Jan 2019, at 03:30, dangleee notifications@github.com wrote:

Whether this model has been published in relevant literature, I hope to see some detailed descriptions of the network in the literature,thanks

— You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub, or mute the thread.

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub, or mute the thread.