While many segmentation approaches exist, most of them are developed for a single, specific imaging modality and a single organ. In clinical practice, however, it is becoming increasingly important to handle multiple modalities: First due to a case-specific choice of the most suitable imaging ...
To this end we introduce PIMMS, a Permutation Invariant Multi-Modal Segmentation technique that is able to perform inference over sets of MRI scans without using modality labels. We present results which show that our convolutional neural network can, in some settings, outperform a baseline model ...
Multi-modality is widely used in medical imaging, because it can provide multiinformation about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing multi-information to improve the segmentation. Recently, deep learning-based approaches have presented the state-of-the...
Video Segmentation from Natural Language Query: 给定一段话(query)与一个视频,分割得到query所指示的物体。 Video-Language Inference: 给定视频(包括视频的一些字幕信息),还有一段文本假设(hypothesis),判断二者是否存在语义蕴含(二分类),即判断视频内容是否包含这段文本的语义。 Object Tracking from Natural Language...
Multi-modality is widely used in medical imaging, because it can provide multiinformation about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing multi-information to improve the segmentation. Recently, deep learning-based approaches have presented the state-of-the...
segmentationmodalityvesselmultimethodangiographic Avesselsegmentationmethod or multi‑modalityangiographicimagesbased on multi‑scaleflteringand statisticalmodels PeiLu 1† ,JunXia 2† ,ZhichengLi 1 ,JingXiong 1 ,JianYang 3 ,ShoujunZhou 1* ,LeiWang 1 ,MingyangChen 1 andChengWang 1 Abstract Back...
实验结果也表明,在缺少某些数据增强的情况下,MVXNet 确实是不能超越 SECOND 的。尤其是在 SECOND 使用了 cut and paste (或者说大家常叫的 GT-sampling)以后,这里也引出了我们的另一点 contribution:multi-modalitycut and paste (MoCa)。 多模态剪切:一骑绝尘...
M3AE: Multimodal Representation Learning for Brain Tumor Segmentation with Missing ModalitiesLiu Hong; WEI DONG; Lu Donghuan; Sun Jinghan; Wang Liansheng; Zheng Yefeng Mx2M: Masked Cross-Modality Modeling in Domain Adaptation for 3D Semantic SegmentationZhang Boxiang; Wang Zunran; Ling Yonggen; ...
We propose a novel learning scheme for unpaired cross-modality image segmentation, with a highly compact architecture achieving superior segmentation accuracy. In our method, we heavily reuse network parameters, by sharing all convolutional kernels across CT and MRI, and only employ modality-specific in...
论文标题:Multi-Modality Task Cascade for 3D Object Detection 作者单位:Carnegie Mellon University 代码:https://github.com/Divadi/MTC_RCNN 论文:https://arxiv.org/pdf/2107.04013.pdf 一句话读论文: 利用2D和3D的信息互补以同时提高2D Segmentation和3D Detection的性能。