Deep learning based neural networks have gained popularity for a variety of biomedical imaging applications. In the last few years several works have shown the use of these methods for colon cancer detection and the early results have been promising. These methods can potentially be utilized to assist doctor's and may help in identifying the number of lesions or abnormalities in a diagnosis session. From our literature survey we found out that there is a lack of publicly available labeled data. Thus, as part of this work, we have aimed at open sourcing a dataset which contains annotations of polyps and ulcers. This is the first dataset that's coming from India containing polyp and ulcer images. The dataset can be used for detection and classification tasks. We also evaluated our dataset with several popular deep learning object detection models that's trained on large publicly available datasets and found out empirically that the model trained on one dataset works well on our dataset that has data being captured in a different acquisition device.

翻译：基于深层学习的神经网络在各种生物医学成像应用方面越来越受欢迎。在过去几年里,一些著作表明使用这些方法来检测结肠癌,早期结果很有希望。这些方法有可能用来帮助医生,并可能有助于确定诊断过程中的损伤或异常数量。我们从文献调查中发现,缺少公开的标签数据。因此,作为这项工作的一部分,我们的目标是打开一个包含聚苯乙烯和溃疡说明的数据集。这是印度第一个包含聚苯和溃疡图像的数据集。数据集可用于检测和分类任务。我们还用几个广受欢迎的深层学习对象检测模型来评估我们的数据集,这些模型经过培训,掌握了大量公开可获取的数据集,并从经验中发现,在单一数据集上培训的模型对不同获取设备中获取的数据集很有帮助。