Datasets and challenges summary of the pathology and blood¶
Pathology & Blood¶
Datasets and challenges summary of pathology-concerned tasks.¶
Tasks include classification (C), segmentation (S), detection (D), tracking (2), counting (1), location (3), nonlinear image registration (4), visual question answering (5).
Index |
Name |
Year |
Focus |
Task |
Stain |
|||
|---|---|---|---|---|---|---|---|---|
233 |
2020 |
visual question answering |
5 |
H&E |
||||
234 |
2020 |
prostate cancer grade assessment |
C |
H&E |
||||
235 |
2020 |
colorectal cancer |
C |
S |
H&E |
|||
236 |
MICCAI 2020 Combined Radiology and Pathology Classification Challenge |
2020 |
combined radiology and pathology classification |
C |
H&E |
|||
237 |
2020 |
HER2 |
C |
H&E |
||||
238 |
2020 |
multi-organ nucleus |
C |
S |
H&E |
|||
239 |
2019 |
cell |
C |
S |
1 |
H&E |
||
240 |
Osteosarcoma data from UT Southwestern/UT Dallas for Viable and Necrotic Tumor Assessment |
2019 |
osteosarcoma pathology image |
C |
H&E |
|||
241 |
Digestive-System Pathological Detection and Segmentation Challenge 2019 |
2019 |
signet ring cell |
C |
S |
D |
H&E |
|
242 |
2019 |
lymphocyte |
D |
3 |
IHC |
|||
243 |
2019 |
pathology image registration |
4 |
|||||
244 |
2019 |
breast cancer metastases to lymph |
D |
H&E |
||||
245 |
2019 |
Gleason grade/score prediction |
C |
H&E |
||||
246 |
2019 |
segmentation of liver cancer & tumor burden |
C |
S |
H&E |
|||
247 |
Automatic Cancer Detection and Classification in Whole-slide Lung Histopathology (ACDC@LUNGHP) |
2019 |
lung cancer |
C |
S |
H&E |
||
248 |
2018 |
multi-organ nucleus |
S |
H&E |
||||
249 |
2018 |
cell |
S |
H&E |
||||
250 |
2019 |
pathology image patch |
C |
H&E |
||||
251 |
2018 |
patch of breast cancer |
C |
H&E |
||||
252 |
2018 |
colorectal pathology patch |
C |
H&E |
||||
254 |
2017 |
breast cancer metastases |
C |
D |
H&E |
|||
253 |
A Grand Challenge for Tissue Microarray Analysis in Thyroid Cancer Diagnosis |
2017 |
thyroid cancer |
C |
H&E |
|||
255 |
2016 |
breast cancer metastases |
C |
D |
H&E |
|||
256 |
2015 |
colorectal cancer pathology patch |
C |
H&E |
||||
257 |
The Second Overlapping Cervical Cytology Image Segmentation Challenge |
2015 |
overlapping cervical cell |
S |
Papanicolaou |
|||
258 |
2014 |
overlapping cervical cell |
S |
Papanicolaou |
||||
259 |
2014 |
mitotic |
D |
H&E |
||||
260 |
2020 |
cell |
2 |
electron microscope |
||||
261 |
2012 |
particle |
2 |
electron microscope |
||||
Datasets and challenges summary of blood concerned tasks.¶
Tasks include classification (C), detection (D), segmentation (1), assessment (2), and stain normalization (3).
Index |
Name |
Year |
Focus |
Task |
Stain |
||
|---|---|---|---|---|---|---|---|
262 |
2020 |
myeloma plasma cell |
1 |
Jenner-Giemsa |
|||
263 |
2020 |
mitochondria |
S |
(electron microscope) |
|||
264 |
A Single-cell Morphological Dataset of Leukocytes from AML Patients and Non-malignant Controls |
2019 |
blast cells in acute myeloid leukaemia |
C |
D |
||
265 |
2019 |
immature leukemic blasts |
C |
D |
|||
266 |
2019 |
cells in blood |
C |
D |
Giemsa |
||
267 |
2019 |
lymphocytes |
2 |
||||
268 |
2019 |
cell |
S |
Jenner-Giemsa |
|||
269 |
SN-AM Dataset: White Blood cancer dataset of B-ALL and MM for stain normalization |
2019 |
stain normalization |
3 |
Jenner-Giemsa |
||
271 |
2018 |
cells in blood |
C |
Jenner-Giemsa |
|||