ISIC：iToBoS 2024 - 基于3D-TBP的皮肤病变检测

数据集获取

源站：https://doi.org/10.34970/561126

标准获取流程：

1. 访问源站链接，注册/登录账号；
2. 进入数据集详情页，按页面指引申请权限或直接下载；
3. 部分平台提供 SDK，例如：
   • OpenDataLab: pip install openxlab 后 openxlab.dataset.get(...)
   • ModelScope: pip install modelscope 后 modelscope download
   • 天池: 登录后页面提供直链下载
     以源站「数据下载/使用文档」页面为准。

数据说明

The iToBoS dataset: skin region images extracted from 3D total body photographs for lesion detection The early detection of skin cancer is critical for improving patient outcomes. Traditionally, dermatologists rely on dermoscopy to examine pigmented skin lesions. While this non-invasive technique enhances diagnostic accuracy, its effectiveness is highly dependent on the clinician’s expertise. Additionally, capturing dermoscopic images for every suspicious lesion is a labor-intensive process. Given these challenges, there is an increasing need for computer-aided diagnosis (CAD) systems that utilize conventional cameras. Such systems can support general physicians and other non-specialist practitioners in identifying potential malignant lesion, improving early detection and intervention. Moreover, they facilitate longitudinal tracking of lesions, aiding researchers in studying disease progression and treatment efficacy. This dataset provides high-resolution skin patch images extracted from 3D total body photographs to support the development of advanced machine learning models for lesion detection. It serves as a valuable resource for researchers working on automated skin lesion analysis, particularly in the context of total body photography (TBP). This dataset contains 59,997 lesion identifying regions-of-interest (ROIs) embedded in 16,954 images stemming from 100 patients. ## Dataset Description: The iToBoS dataset consists of 16,954 high-resolution images of skin regions obtained from anonymized 3D avatars of patients. These avatars were generated using the Canfield VECTRA WB360 system, a cutting-edge imaging technology that captures comprehensive, full-body skin images using 92 fixed cameras arranged in 46 stereo pairs with xenon flash lighting. The images were collected from patients at two clinical sites: the Clinical Hospital of Barcelona (Spain) (n=7,729) and the University of Queensland (Australia) (n=9,225). The dataset provides diverse anatomical locatio

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。