找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017; 20th International C Maxime Descoteaux,Lena Maier-Hein,Simon Duch

[复制链接]
楼主: 投降
发表于 2025-3-28 17:19:46 | 显示全部楼层
0302-9743 tions; interventional imaging and navigation; and medical image computing. Part III: feature .extraction and classification techniques; and machine learning in medical image computing.978-3-319-66184-1978-3-319-66185-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
发表于 2025-3-28 21:17:48 | 显示全部楼层
Cell Lineage Tracing in Lens-Free Microscopy Videoser progression and its treatment. While recent progress in lens-free microscopy (LFM) has rendered it an inexpensive tool for continuous monitoring of these experiments, there is only little work on analysing such time-lapse sequences..We propose (1) a cell detector for LFM images based on residual
发表于 2025-3-29 02:38:11 | 显示全部楼层
发表于 2025-3-29 03:03:54 | 显示全部楼层
发表于 2025-3-29 10:12:03 | 显示全部楼层
Cell Encoding for Histopathology Image Classifications is time consuming and expensive. Meanwhile, with the development of cell detection and segmentation techniques, it is possible to classify pathology images by using cell-level information, which is crucial to grade different diseases; however, it is still very challenging to efficiently conduct ce
发表于 2025-3-29 11:33:42 | 显示全部楼层
发表于 2025-3-29 16:43:18 | 显示全部楼层
发表于 2025-3-29 20:17:56 | 显示全部楼层
Two-Stream Bidirectional Long Short-Term Memory for Mitosis Event Detection and Stage Localization iin time-lapse phase contrast microscopy image sequences. Our method consists of two steps. First, we extract candidate mitosis image sequences. Then, we solve the problem of mitosis event detection and stage localization jointly by the proposed TS-BLSTM, which utilizes both appearance and motion inf
发表于 2025-3-30 01:57:37 | 显示全部楼层
发表于 2025-3-30 07:20:43 | 显示全部楼层
Semi-supervised Segmentation of Optic Cup in Retinal Fundus Images Using Variational Autoencoderlaucoma assessment. The ill-defined boundaries of optic cup makes the segmentation a lot more challenging compared to optic disc. Existing approaches have mainly used fully supervised learning that requires many labeled samples to build a robust segmentation framework. In this paper, we propose a no
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-10 23:47
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表