The objective is to extract the extra space to find the malignant area. The image has been observed and extracted with various methodologies to find the exact nuclei of the cancer cells. Koilocytes cells were taken into consideration of analysis and super pixels segmentation. The malignant cells were found out by extracting and eliminating the background space of the cervical image to get a clear picture of the affected cervical cells. The nuclei cells were segmented to get positive and negative values. The original images were extracted by removing the background spaces and the cytoplasm of the cervical region. The squamous and basal cells were determined by eliminating unwanted cytoplasm. The super pixel cells were taken for the analysis. The method was designed the framework with the series of segmentation and extracting the core nuclei to extract the unwanted space to find the malignant area. Stage 0 explains about the cancer cells find out in the surface of the cervix. More invasive cancers are differentiated into four stages. Stage I—if cancer grows beyond the surface of the cervix and the uterus without affecting the outer region i.e., Walls of the pelvis or the vagina’s bottom surface. Stage II describes the cancer cells has been spread beyond the cervix surface and uterus and possibly to nearby tissue. Stage III cancer considered as a severe type of cancer. The cancer cells were spread to the lower part of the vagina and sometime it will stop the urine flow. Stage IV clearly defines the most advanced stage of cervical cancer. It will affect all the organs of the body. The affected cells were extended to the organs of the human body. The detected malignant cells were divided into segmentation. If the segmentation of each frame contains a malignant cell, then it will be marked as positive and if the frame doesn’t have a malignant cell, then it will be marked as negative. By analysing the segmentation and extraction it can be easily find out the number of malignant cells in the region. In our proposed methodology the original image was undergone into various slides of the Pap smear test. By the positive and the negative values of the core nuclei the growth and the severity of the malignant cells can be pictured. Through the results, the treatment can be easily carried out according to the stages of severity.

目的是提取额外的空间以找到恶性区域。已经观察到图像并用各种方法提取图像以找到癌细胞的确切细胞核。红细胞细胞被考虑到分析和超像素分割。通过提取并消除子宫颈图像的背景空间，找出受影响的子宫颈细胞的清晰图​​片，找出恶性细胞。分割核细胞以获得正值和负值。通过去除背景空间和宫颈区域的细胞质来提取原始图像。通过消除不需要的细胞质来确定鳞状和基底细胞。将超像素单元用于分析。该方法设计了一系列分割和提取核心核的框架，以提取不需要的空间以找到恶性区域。阶段0解释了在子宫颈表面发现的癌细胞。更具侵入性的癌症分为四个阶段。第一阶段-如果癌症扩散到子宫颈和子宫表面之外而又不影响外部区域（即骨盆壁或阴道底表面）。第二阶段描述癌细胞已经扩散到子宫颈表面和子宫之外，并可能扩散到附近的组织。III期癌症被认为是严重的癌症类型。癌细胞扩散到阴道下部，有时它会阻止尿液流动。第四阶段明确定义了宫颈癌的最晚期。它会影响身体的所有器官。受影响的细胞扩展到人体器官。将检测到的恶性细胞分成分割。如果每个帧的分段包含一个恶性细胞，则将其标记为正；如果该帧没有恶性细胞，则将其标记为负。通过分析分割和提取，可以轻松找出该区域中恶性细胞的数量。在我们提出的方法中，原始图像经过了子宫颈抹片检查的各种幻灯片。通过核心核的正值和负值，可以观察到恶性细胞的生长和严重程度。通过结果，可以根据严重程度轻松地进行治疗。将检测到的恶性细胞分成分割。如果每个帧的分段包含一个恶性细胞，则将其标记为正；如果该帧没有恶性细胞，则将其标记为负。通过分析分割和提取，可以轻松找出该区域中恶性细胞的数量。在我们提出的方法中，原始图像经过了子宫颈抹片检查的各种幻灯片。通过核心核的正值和负值，可以观察到恶性细胞的生长和严重程度。通过结果，可以根据严重程度轻松地进行治疗。将检测到的恶性细胞分成分割。如果每个帧的分段包含一个恶性细胞，则将其标记为正；如果该帧没有恶性细胞，则将其标记为负。通过分析分割和提取，可以轻松找出该区域中恶性细胞的数量。在我们提出的方法中，原始图像经过了子宫颈抹片检查的各种幻灯片。通过核心核的正值和负值，可以观察到恶性细胞的生长和严重程度。通过结果，可以根据严重程度轻松地进行治疗。那么它将被标记为否定。通过分析分割和提取，可以轻松找出该区域中恶性细胞的数量。在我们提出的方法中，原始图像经过了子宫颈抹片检查的各种幻灯片。通过核心核的正值和负值，可以观察到恶性细胞的生长和严重程度。通过结果，可以根据严重程度轻松地进行治疗。那么它将被标记为否定。通过分析分割和提取，可以轻松找出该区域中恶性细胞的数量。在我们提出的方法中，原始图像经过了子宫颈抹片检查的各种幻灯片。通过核心核的正值和负值，可以观察到恶性细胞的生长和严重程度。通过结果，可以根据严重程度轻松地进行治疗。