A system and method of diagnosing gastrointestinal neoplasm or pathologies in an endoscopy system including an endoscopy system display for displaying an image enhanced endoscopy (IEE) image. The method includes randomly generating training image samples with or without cancer region(s) by an adversarial network (AN) including collecting endoscopic training images (T1) and automatically generating a realistic IEE image as a new training image sample (T2) using a generator network in the AN from a generated segmentation map； using a prediction network (L1PN) to learn a level 1 prediction result being a cancerous probability of an IEE image from the collected T1 and T2； using a prediction network (L2PN) to learn a level 2 prediction result being detected cancerous region(s) of an IEE image； and predicting the level 1 result and the level 2 result for an IEE image using the L1PN and the L2PN and without using the AN.一種於內視鏡檢查系統中診斷胃腸道腫瘤或病理的系統及方法，該內視鏡檢查系統包含用於顯示圖像增強內視鏡(IEE)圖像的一內視鏡系統顯示器。該方法包含藉由一對抗網絡(AN)隨機生成具有或不具有癌症區域的訓練圖像樣本，該對抗網絡包含收集內視鏡訓練圖像(T1)並使用來自一生成分段地圖的該AN中的一生成器，自動生成一逼真的IEE圖像作為一新的訓練圖像樣本(T2)；使用一預測網絡(L1PN)從該所收集的T1及該T2，學習一1級預測結果，該1級預測結果為一IEE圖像的一癌變概率；使用一預測網絡(L2PN)學習一2級預測結果，該2級預測結果為一IEE圖像所偵測到的癌變區域；及使用該L1PN及該L2PN並且不使用AN，預測IEE圖像的該1級結果及該2級結果。
