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CPIA_data_process

The CPIA dataset contains 3,474,406 (the total number is growing as we continue to process the datasets) standardized images, covering over 50 organs/tissues and about 98 kinds of diseases, which includes two main data types: whole slide images (WSIs) and characteristic regions of interest (ROIs).

In this repo, we provide relevant codes for processing all sub-datasets within the CPIA dataset.

image The compositions and WSI processing strategy of the CPIA dataset.

image The multi-scale strategy and diverse characteristics of the CPIA dataset.

WSI

Each WSI dataset is divided into four levels using one python program. Most of the Whole Slide Imaging (WSI) images are stored in the SVS format, which includes the micron-per-pixel (MPP) information in the header file. Our processing program can automatically identify the MPP of each image and standardize it to 0.4942um/pixel by adjusting the edge length of each patch. Finally, the patch images are divided into four different sizes with edge lengths of 3840, 960, 384, and 96, respectively, and stored in their respective folders.

Sub-dataset name Process Code Suffix
CAM16 CPIA_WSI tif
CATCH dataset CPIA_WSI svs
CMB-CRC CPIA_WSI svs
CMB-LCA CPIA_WSI svs
CMB-MEL CPIA_WSI svs
CPTAC-AML CPIA_WSI svs
CPTAC-BRCA CPIA_WSI svs
CPTAC-CCRCC CPIA_WSI svs
CPTAC-CM CPIA_WSI svs
CPTAC-COAD CPIA_WSI svs
CPTAC-HNSCC CPIA_WSI svs
CPTAC-LSCC CPIA_WSI svs
CPTAC-LUAD CPIA_WSI svs
CPTAC-OV CPIA_WSI svs
CPTAC-PDA CPIA_WSI svs
CPTAC-SAR CPIA_WSI svs
CPTAC-UCEC CPIA_WSI svs
HER2 tumor ROIs CPIA_WSI svs
MSKCC(SLN-Breast) CPIA_WSI svs
PAIP2019 CPIA_WSI svs
PAIP2020 CPIA_WSI svs
PAIP2021 CPIA_WSI svs
Post-NAT-BRCA CPIA_WSI svs
TCGA-ACC CPIA_WSI svs
TCGA-BLCA CPIA_WSI svs
TCGA-BRCA CPIA_WSI svs
TCGA-CESC CPIA_WSI svs
TCGA-CHOL CPIA_WSI svs
TCGA-COAD CPIA_WSI svs
TCGA-DLBC CPIA_WSI svs
TCGA-ESCA CPIA_WSI svs
TCGA-GBM CPIA_WSI svs
TCGA-HNSC CPIA_WSI svs
TCGA-KICH CPIA_WSI svs
TCGA-KIRC CPIA_WSI svs
TCGA-KIRP CPIA_WSI svs
TCGA-LGG CPIA_WSI svs
TCGA-LIHC CPIA_WSI svs
TCGA-LUAD CPIA_WSI svs
TCGA-LUSC CPIA_WSI svs
TCGA-MESO CPIA_WSI svs
TCGA-OV CPIA_WSI svs
TCGA-PAAD CPIA_WSI svs
TCGA-PCPG CPIA_WSI svs
TCGA-PRAD CPIA_WSI svs
TCGA-READ CPIA_WSI svs
TCGA-SARC CPIA_WSI svs
TCGA-SKCM CPIA_WSI svs
TCGA-STAD CPIA_WSI svs
TCGA-TGCT CPIA_WSI svs
TCGA-THCA CPIA_WSI svs
TCGA-THYM CPIA_WSI svs
TCGA-UCEC CPIA_WSI svs
TCGA-UCS CPIA_WSI svs
TCGA-UVM CPIA_WSI svs

ROI

The processing code for the ROI dataset is related to the structure of the original dataset. After the processing is complete, each dataset folder contains only all images of that dataset, with each image having a dimension of 384x384 pixels, and is stored in jpg format.

Before processing the data, please ensure that only the target images to be processed are contained in the input path of the program, and enter the correct suffix of the images to be processed (this might require slight adjustments to the original dataset folder).

Sub-dataset name Process Code Suffix Add_class
ANHIR CPIA_ROI_1_Crop&Resize png FALSE
BCSS CPIA_ROI_1_Crop&Resize png FALSE
AML_Cytomorphology CPIA_ROI_1_Crop&Resize tiff FALSE
BCCD CPIA_ROI_1_Crop&Resize jpg FALSE
Blood_Cell_Images CPIA_ROI_1_Crop&Resize jpg TRUE
BreakHis CPIA_ROI_0_BreakHis + CPIA_ROI_1_Crop&Resize jpg TRUE
Breast_Histopathology_Images CPIA_ROI_1_Crop&Resize png FALSE
BreastCancerCells CPIA_ROI_1_Crop&Resize tif FALSE
BreastPathQ CPIA_ROI_1_Crop&Resize tif FALSE
BreCaHAD CPIA_ROI_1_Crop&Resize tif FALSE
Chaoyang CPIA_ROI_1_Crop&Resize jpg FALSE
Colorectal Histology MNIST CPIA_ROI_1_Crop&Resize tif FALSE
CoNSeP CPIA_ROI_1_Crop&Resize png FALSE
CPM_15 CPIA_ROI_1_Crop&Resize png FALSE
CPM_17 CPIA_ROI_1_Crop&Resize png TRUE
CRAG CPIA_ROI_1_Crop&Resize jpg FALSE
CRChistophenotypes CPIA_ROI_1_Crop&Resize bmp FALSE
CRC-TP CPIA_ROI_1_Crop&Resize png TRUE
CRC-VAL-HE-7K CPIA_ROI_1_Crop&Resize jpg FALSE
CryoNuSeg CPIA_ROI_1_Crop&Resize tif FALSE
DataBiox CPIA_ROI_1_MicroScope DataBiox jpg FALSE
GasHisSDB CPIA_ROI_0_GasHisSDB + CPIA_ROI_1_Crop&Resize jpg FALSE
Gastrointestinal_Cancer CPIA_ROI_1_Crop&Resize jpg FALSE
Gleason 2019 CPIA_ROI_1_Crop&Resize jpg FALSE
HuBMAP+HBA_512 CPIA_ROI_1_Crop&Resize png FALSE
Kumar(MoNuSeg) CPIA_ROI_1_Crop&Resize tif FALSE
LISC CPIA_ROI_1_Crop&Resize bmp FALSE
LizardDataset CPIA_ROI_1_Crop&Resize png FALSE
Lung_and_Colon_Cancer_Histopathological_Images_Colon CPIA_ROI_1_Crop&Resize jpg TRUE
Lung_and_Colon_Cancer_Histopathological_Images_Lung CPIA_ROI_1_Crop&Resize jpg TRUE
LYON19 CPIA_ROI_1_Crop&Resize png FALSE
Malignant_Lymphoma_Dataset CPIA_ROI_1_Crop&Resize tif FALSE
MARS CPIA_ROI_1_Crop&Resize png FALSE
MHIST CPIA_ROI_1_Crop&Resize png FALSE
MoNuSAC CPIA_ROI_1_Crop&Resize tif FALSE
Monuseg_train&test CPIA_ROI_1_Crop&Resize png FALSE
Naylor et al, IEEE TMI 2019 CPIA_ROI_1_Crop&Resize png FALSE
NCT-CRC-HE-100K CPIA_ROI_1_Crop&Resize tif FALSE
Osteosarcoma_Tumor_Assessment CPIA_ROI_1_Crop&Resize jpg FALSE
P_falciparum CPIA_ROI_1_MicroScope P.falciparum jpg FALSE
P_uninfected CPIA_ROI_1_MicroScope P.uninfected jpg FALSE
P_vivax CPIA_ROI_1_MicroScope P.vivax jpg FALSE
PCam CPIA_ROI_1_Crop&Resize tif FALSE
SICAPv2 CPIA_ROI_1_Crop&Resize jpg FALSE
SIPaKMeD CPIA_ROI_0_SIPaKMeD + CPIA_ROI_1_Crop&Resize jpg FALSE
warwick_CLS CPIA_ROI_0_Warwick + CPIA_ROI_1_Crop&Resize jpg FALSE
WBC CPIA_ROI_1_Crop&Resize jpg TRUE
Weinart et al, Scientific Reports 2012 CPIA_ROI_1_Crop&Resize jpg FALSE
WSSS4LUAD CPIA_ROI_1_Crop&Resize png TRUE

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