Early detection of cervical cancer is key to detecting and treating cancer. Applying the
computer to the detection of cervical cancer can get more accurate results. However, data …

Cervical cancer is the fourth most common gynecological malignant cancer in the world. It
presents one of the principal causes of cancer death in women. Treatment planning …

The survival rate of cervical cancer can be improved by the early screening. However, the
screening is a heavy task for pathologists. Thus, automatic cervical cell classification model …

The segmentation of cervical cell in liquid-based smear image plays an important role in
cervical cancer detection. Despite of research for many years, it is still a challenge for the …

The detection and classification of cervical cells via Pap smear or Liquid-based cytology
(LBC) have important clinical significance for pathological diagnosis. For the limitations of …

The screening and diagnosis of cervical lesions can effectively reduce the risk of cervical
cancer. At present, there are few research algorithms and models for colposcopy in cervical …

With the widely applied computer-aided diagnosis techniques in cervical cancer screening,
cell segmentation has become a necessary step to determine the progression of cervical …

Cervical cancer is the fourth most common cancer in the world. Whole-slide images (WSIs)
are an important standard for the diagnosis of cervical cancer. Missed diagnoses and …

Recently, deep learning methods, in particular, convolutional neural networks (CNNs), have
made a massive breakthrough in computer vision. And a big amount of annotated data is the …

Cervical cancer affects 570,000 women globally and is among the most common causes of
cancer-related deaths. Cervical cancer is caused due to the Human Papilloma Virus (HPV) …