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BreakHis
许可协议: CC-BY-SA 4.0

Overview

Context

The Breast Cancer Histopathological Image Classification (BreakHis) is composed of 9,109 microscopic images of breast tumor tissue collected from 82 patients using different magnifying factors (40X, 100X, 200X, and 400X). To date, it contains 2,480 benign and 5,429 malignant samples (700X460 pixels, 3-channel RGB, 8-bit depth in each channel, PNG format). This database has been built in collaboration with the P&D Laboratory – Pathological Anatomy and Cytopathology, Parana, Brazil (http://www.prevencaoediagnose.com.br). We believe that researchers will find this database a useful tool since it makes future benchmarking and evaluation possible.

Content

The dataset BreaKHis is divided into two main groups: benign tumors and malignant tumors. Histologically benign is a term referring to a lesion that does not match any criteria of malignancy – e.g., marked cellular atypia, mitosis, disruption of basement membranes, metastasize, etc. Normally, benign tumors are relatively “innocents”, presents slow growing and remains localized. Malignant tumor is a synonym for cancer: lesion can invade and destroy adjacent structures (locally invasive) and spread to distant sites (metastasize) to cause death.

In current version, samples present in dataset were collected by SOB method, also named partial mastectomy or excisional biopsy. This type of procedure, compared to any methods of needle biopsy, removes the larger size of tissue sample and is done in a hospital with general anesthetic.

Both breast tumors benign and malignant can be sorted into different types based on the way the tumoral cells look under the microscope. Various types/subtypes of breast tumors can have different prognoses and treatment implications. The dataset currently contains four histological distinct types of benign breast tumors: adenosis (A), fibroadenoma (F), phyllodes tumor (PT), and tubular adenona (TA); and four malignant tumors (breast cancer): carcinoma (DC), lobular carcinoma (LC), mucinous carcinoma (MC) and papillary carcinoma (PC).

Each image filename stores information about the image itself: method of procedure biopsy, tumor class, tumor type, patient identification, and magnification factor. For example, SOB_B_TA-14-4659-40-001.png is the image 1, at magnification factor 40X, of a benign tumor of type tubular adenoma, original from the slide 14-4659, which was collected by procedure SOB. More formally, the format of image file name is given by the following BNF notation:

数据概要
数据格式
image,
数据量
7.924K
文件大小
510.09MB
发布方
Bukun
| 数据量 7.924K | 大小 510.09MB
BreakHis
许可协议: CC-BY-SA 4.0

Overview

Context

The Breast Cancer Histopathological Image Classification (BreakHis) is composed of 9,109 microscopic images of breast tumor tissue collected from 82 patients using different magnifying factors (40X, 100X, 200X, and 400X). To date, it contains 2,480 benign and 5,429 malignant samples (700X460 pixels, 3-channel RGB, 8-bit depth in each channel, PNG format). This database has been built in collaboration with the P&D Laboratory – Pathological Anatomy and Cytopathology, Parana, Brazil (http://www.prevencaoediagnose.com.br). We believe that researchers will find this database a useful tool since it makes future benchmarking and evaluation possible.

Content

The dataset BreaKHis is divided into two main groups: benign tumors and malignant tumors. Histologically benign is a term referring to a lesion that does not match any criteria of malignancy – e.g., marked cellular atypia, mitosis, disruption of basement membranes, metastasize, etc. Normally, benign tumors are relatively “innocents”, presents slow growing and remains localized. Malignant tumor is a synonym for cancer: lesion can invade and destroy adjacent structures (locally invasive) and spread to distant sites (metastasize) to cause death.

In current version, samples present in dataset were collected by SOB method, also named partial mastectomy or excisional biopsy. This type of procedure, compared to any methods of needle biopsy, removes the larger size of tissue sample and is done in a hospital with general anesthetic.

Both breast tumors benign and malignant can be sorted into different types based on the way the tumoral cells look under the microscope. Various types/subtypes of breast tumors can have different prognoses and treatment implications. The dataset currently contains four histological distinct types of benign breast tumors: adenosis (A), fibroadenoma (F), phyllodes tumor (PT), and tubular adenona (TA); and four malignant tumors (breast cancer): carcinoma (DC), lobular carcinoma (LC), mucinous carcinoma (MC) and papillary carcinoma (PC).

Each image filename stores information about the image itself: method of procedure biopsy, tumor class, tumor type, patient identification, and magnification factor. For example, SOB_B_TA-14-4659-40-001.png is the image 1, at magnification factor 40X, of a benign tumor of type tubular adenoma, original from the slide 14-4659, which was collected by procedure SOB. More formally, the format of image file name is given by the following BNF notation:

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