UW-Madison GI Tract Image Segmentation 数据集 是一个用于磁共振成像 (MRI) 中大小肠及胃部分割的医学影像数据集。该数据集由威斯康星大学麦迪逊分校放射肿瘤科提供,包含 38496 张图像,共分为 3 个类别:小肠、大肠和胃。目前开放下载的为训练集。该数据的图像文件名包含4个数字(如 276_276_1.63_1.63.png)。这...
这将使癌症患者的日常治疗更快,让他们获得更有效的治疗、更少的副作用和更好的长期癌症控制。 二、UW-Madison GI Tract Image Segmentation2022任务 MRI 扫描中自动分割胃和肠道。 三、UW-Madison GI Tract Image Segmentation2022数据集 训练注释以RLE编码蒙版形式提供,图像采用 16 位灰度 PNG 格式。每个案例都由...
Al-Dhabyani, W., Gomaa, M., Khaled, H., Fahmy, A.: Dataset of breast ultrasound images. Data Brief 28, 104863 (2020) Google Scholar Cortinhas, S.: Apples or tomatoes. Online available at: https://www.kaggle.com/datasets/samuelcortinhas/apples-or-tomatoes-image-classification Bloch...
One head is for predicting boxes and the other is for classifying them as object or background (we are not predicting segmentation masks yet). The RPN has its own loss function, computed from a slightly modified training dataset: the class of any ground truth object is replaced with a ...
Recently, medical image segmentation research has shown that there are mainly three solutions: (1) U-shape method. The U-shape method can reduce the loss caused by spatial changes to a certain extent through deep mapping and skip connection structure and can learn deep semantic information. UNet...
ImageNet 2017 挑战赛是最后一届，李飞飞在 CVPR 2017 上表明 ImageNet 挑战赛以后将与 Kaggle 结合。她在演讲中欣喜地表明她们正在将接力棒传递给 Kaggle，不仅因为 Kaggle 社区是最大的数据科学社区，同时还因为她们认为只有将数据做到民主化才能实现 AI 民主化。虽然 ImageNet 挑战赛是最后一届了，但 image-net...
chenjun2hao/segmentation.pytorch: Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset (github.com) 这是一个PyTorch实现的在MIT ADE20K场景解析数据集上的语义分割模型 This is a PyTorch implementation of semantic segmentation models on MIT ADE20K scene parsing dataset (http...
A dataset provided by Kaggle comprising brain MR images has been used in training and testing the model. The image segmentation results are compared with the K-means clustering method using various performance metrics. The maximum accuracy of 91.18% has been observed at 350 epochs by the proposed...
https://www.kaggle.com/datasets/hsankesara/flickr-image-dataset COCO: https://cocodataset.org/ Conceptual Captions: https://ai.google.com/research/ConceptualCaptions/ LSVTD: https://davar-lab.github.io/dataset/lsvtd.html WebVid: https://github.com/m-bain/webvid ...
Lung Segmentation 1- Download the Lung Segmentation dataset from Kaggle link and extract it. 2- Run Prepare_data.py for data preperation, train/test seperation and generating new masks around the lung tissues. 3- Run train_lung.py for training BCDU-Net model using trainng and validation set...