钼钯

数据格式

{ # 一个pid对应的四张片子为一组，保存再一个json中
'patientID': pid
'studyUID': studyid
'seriesUID' : seriesid
'json_format_version':2.0
'quality' : 0
'pixel_spacing' : np.array([0.085, 0.085]).tolist() # 从dcm中提取得到
'task': task_name
'other_info': {}
'nodes': {
        "node_index": "1", # 病灶序号，钙化和肿块依次标号
        "score": 0.0, # 检出的打分
        "note": "",
        "from": 0b100,
        "type": "Breast_Calcification", # 病灶类型："Breast_Calcification"（钙化）或者 "Breast_Lump"（肿块）
        "attr": {},
        "bounds": [ # 存储检出的bbox：钙化和肿块都有
            {
                "slice_index": 0, # instance id
                "edge": [] # bbox的四个点的座标（x, y）
            }
        ],
        "rois": [ # 存储检出的分割segms：只有肿块有
            {
                "slice_index": 0, # instance id
                "edge": [] #分割contour上所有点的座标 (x, y)
            }
        ],
    }
}

保存

import copy
def __make_json_result(series_list, pid, studyid, seriesid, mass_list, task_name='BreastMGDetect'):
    node = {
        "node_index": "1", 
        "score": 0.0,
        "note": "",
        "from": 0b100,
        "type": "Breast_Calcification", 
        "attr": {},
        "bounds": [
            {
                "slice_index": 0,
                "edge": []
            }
        ],
        "rois": [
            {
                "slice_index": 0,
                "edge": []
            }
        ],
    }

    ret = {}
    ret['patientID'] = pid
    ret['studyUID'] = studyid
    ret['seriesUID'] = seriesid
    ret['json_format_version'] = 2.0
    ret['quality'] = 0
    ret['pixel_spacing'] = np.array([0.085, 0.085]).tolist()
    ret['task'] = task_name
    ret['other_info'] = {}
    roi_list = []
    for series, masses in zip(series_list, mass_list): 
        bboxes = masses['bboxes']
        segms = masses['segms']
        calc_num = 0
        for i, item in enumerate(bboxes):
            x1, y1, x2, y2 = item[:4]
            score = item[-1]
            points = np.int32([[x1, y1], [x2, y1], [x2, y2], [x1, y2]]).tolist()
            nodule = copy.deepcopy(node)
            nodule['type'] = "Breast_Lump"
            nodule['node_index'] = str(i + 1 + calc_num)
            nodule['score'] = str(score)
            edges = np.int32(segms[i]).tolist()
            nodule['rois'][0]['edge'] = [[y, x] for (x, y) in edges]
            nodule['rois'][0]['slice_index'] = series
            nodule['bounds'][0]['edge'] = points
            nodule['bounds'][0]['slice_index'] = series
            roi_list.append(nodule)

    ret['nodes'] = roi_list
    return json.dumps(ret), "OK"