diff --git a/photo_review/auto_photo_review.py b/photo_review/auto_photo_review.py
index 89cbd2f..a0ee475 100644
--- a/photo_review/auto_photo_review.py
+++ b/photo_review/auto_photo_review.py
@@ -1,6 +1,7 @@
 import json
 import logging
 import os
+import re
 import shutil
 import time
 import uuid
@@ -8,7 +9,6 @@ from collections import defaultdict
 from time import sleep
 
 import cv2
-import fitz
 import jieba
 import numpy as np
 import zxingcpp
@@ -21,44 +21,48 @@ from log import HOSTNAME
 from photo_review import PHHD_BATCH_SIZE, SLEEP_MINUTES, HOSPITAL_ALIAS, HOSPITAL_FILTER, DEPARTMENT_ALIAS, \
     DEPARTMENT_FILTER, DISCHARGE_KEY, set_batch_id, get_batch_id
 from services.paddle_services import IE_KEY
-from ucloud import ufile
+from ucloud import ufile, BUCKET
 from util import image_util, common_util, html_util, model_util
 from util.data_util import handle_date, handle_decimal, parse_department, handle_name, handle_insurance_type, \
     handle_original_data, handle_hospital, handle_department, handle_id, handle_age, parse_money, parse_hospital, \
     parse_page_num, handle_tiny_int
 
 
-# 尝试从二维码中获取高清图片
-def get_better_image_from_qrcode(img_path, image_id, dpi=150):
+def parse_qrcode(img_path, image_id):
+    """
+    解析二维码，尝试从中获取高清图片
+    :param img_path: 待解析图片
+    :param image_id: 图片id
+    :return: 解析结果
+    """
+
     def _parse_pdf_url(pdf_url_to_parse):
-        pdf_file = None
         local_pdf_path = None
+        img_name, img_ext = common_util.parse_save_path(img_path)
         try:
             local_pdf_path = html_util.download_pdf(pdf_url_to_parse)
-            # 打开PDF文件
-            pdf_file = fitz.open(local_pdf_path)
-            # 选择第一页
-            page = pdf_file[0]
-            # 定义缩放系数（DPI）
-            default_dpi = 72
-            zoom = dpi / default_dpi
-            # 设置矩阵变换参数
-            mat = fitz.Matrix(zoom, zoom)
-            # 渲染页面
-            pix = page.get_pixmap(matrix=mat)
-            # 将渲染结果转换为OpenCV兼容的格式
-            img = np.frombuffer(pix.samples, dtype=np.uint8).reshape((pix.height, pix.width, -1))
-            img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
-            img_name, img_ext = common_util.parse_save_path(img_path)
-            better_img_path = common_util.get_processed_img_path(f'{img_name}.better.{img_ext}')
-            cv2.imwrite(better_img_path, img)
-            return better_img_path, page.get_text()
+            pdf_imgs = image_util.pdf_to_imgs(local_pdf_path)
+            # 结算单部分
+            better_settlement_path = common_util.get_processed_img_path(f'{img_name}.better_settlement.jpg')
+            cv2.imwrite(better_settlement_path, pdf_imgs[0][0])
+            # 费用清单部分
+            better_cost_path = common_util.get_processed_img_path(f'{img_name}.better_cost.jpg')
+            total_height = sum([p[0].shape[0] for p in pdf_imgs[1:]])
+            common_width = pdf_imgs[1][0].shape[1]
+            better_cost_img = np.zeros((total_height, common_width, 3), dtype=np.uint8)
+            current_y = 0
+            for pdf in pdf_imgs[1:]:
+                height = pdf[0].shape[0]
+                better_cost_img[current_y:current_y + height, :, :] = pdf[0]
+                current_y += height
+                # cost_text += pdf[1]  # 费用清单文本暂时没用到
+            cv2.imwrite(better_cost_path, better_cost_img)
+
+            return better_settlement_path, pdf_imgs[0][1], better_cost_path
         except Exception as ex:
             logging.getLogger('error').error('解析pdf失败！', exc_info=ex)
-            return None, None
+            return None, None, None
         finally:
-            if pdf_file:
-                pdf_file.close()
             if local_pdf_path:
                 common_util.delete_temp_file(local_pdf_path)
 
@@ -99,7 +103,7 @@ def get_better_image_from_qrcode(img_path, image_id, dpi=150):
             logging.getLogger('error').error('从二维码中获取高清图片时出错', exc_info=e)
             continue
 
-    return None, None
+    return None, None, None
 
 
 # 关键信息提取
@@ -110,61 +114,48 @@ def information_extraction(phrec, pk_phhd):
     :param pk_phhd:案子主键
     :return:记录类型，信息抽取结果
     """
-    original_img_path = common_util.get_img_path(phrec.cfjaddress)
-    if not original_img_path:
-        img_url = ufile.get_private_url(phrec.cfjaddress)
-        if not img_url:
-            return None, None, None
-        original_img_path = common_util.save_to_local(img_url)
     img_path = common_util.get_processed_img_path(phrec.cfjaddress)
-    shutil.copy2(original_img_path, img_path)
+    if image_util.is_photo(img_path):
+        book_img_path = model_util.det_book(img_path)  # 识别文档区域并裁剪
+        dewarped_img_path = model_util.dewarp(book_img_path)  # 去扭曲
+    else:  # todo:也可能是图片，后续添加细分逻辑
+        dewarped_img_path = img_path
+    angles = model_util.clas_orientation(dewarped_img_path)
+    ocr_text = ''
+    info_extract = []
+    rec_type = None
+    for angle in angles:
+        ocr_result = []
+        rotated_img = image_util.rotate(dewarped_img_path, int(angle))
+        split_results = image_util.split(rotated_img)
+        for split_result in split_results:
+            if split_result['img'] is None:
+                continue
+            a4_img = image_util.expand_to_a4_size(split_result['img'])
+            ocr_result += model_util.ocr(a4_img)
+        tmp_ocr_text = common_util.ocr_result_to_text(ocr_result)
 
-    # 尝试从二维码中获取高清图片
-    better_img_path, text = get_better_image_from_qrcode(img_path, phrec.cfjaddress)
-    if phrec.cRectype != '1':
-        better_img_path = None  # 非结算单暂时不进行替换
-    if better_img_path is not None:
-        rec_type = '基本医保结算单'
-        if text:
-            info_extract = model_util.ie_settlement_text(text)
+        tmp_rec_type = model_util.clas_text(tmp_ocr_text) if ocr_text else None
+        if not tmp_rec_type:
+            rec_dict = {
+                '1': '基本医保结算单',
+                '3': '出院记录',
+                '4': '费用清单',
+            }
+            tmp_rec_type = rec_dict.get(phrec.cRectype)
+        if tmp_rec_type == '基本医保结算单':
+            tmp_info_extract = model_util.ie_settlement(rotated_img, common_util.ocr_result_to_layout(ocr_result))
+        elif tmp_rec_type == '出院记录':
+            tmp_info_extract = model_util.ie_discharge(rotated_img, common_util.ocr_result_to_layout(ocr_result))
+        elif tmp_rec_type == '费用清单':
+            tmp_info_extract = model_util.ie_cost(rotated_img, common_util.ocr_result_to_layout(ocr_result))
         else:
-            info_extract = model_util.ie_settlement(
-                better_img_path, common_util.ocr_result_to_layout(model_util.ocr(better_img_path))
-            )
-        ocr_text = None  # 此处肯定不是出院记录，后续用不到
-    else:
-        if image_util.is_photo(img_path):
-            book_img_path = model_util.det_book(img_path)  # 识别文档区域并裁剪
-            dewarped_img_path = model_util.dewarp(book_img_path)  # 去扭曲
-        else:  # todo:也可能是图片，后续添加细分逻辑
-            dewarped_img_path = img_path
-        angles = model_util.clas_orientation(dewarped_img_path)
-        ocr_text = ''
-        info_extract = []
-        for angle in angles:
-            ocr_result = []
-            rotated_img = image_util.rotate(dewarped_img_path, int(angle))
-            split_results = image_util.split(rotated_img)
-            for split_result in split_results:
-                if split_result['img'] is None:
-                    continue
-                a4_img = image_util.expand_to_a4_size(split_result['img'])
-                ocr_result += model_util.ocr(a4_img)
-            tmp_ocr_text = common_util.ocr_result_to_text(ocr_result)
+            tmp_info_extract = []
 
-            rec_type = model_util.clas_text(tmp_ocr_text) if ocr_text else None
-            if rec_type == '基本医保结算单':
-                tmp_info_extract = model_util.ie_settlement(rotated_img, common_util.ocr_result_to_layout(ocr_result))
-            elif rec_type == '出院记录':
-                tmp_info_extract = model_util.ie_discharge(rotated_img, common_util.ocr_result_to_layout(ocr_result))
-            elif rec_type == '费用清单':
-                tmp_info_extract = model_util.ie_cost(rotated_img, common_util.ocr_result_to_layout(ocr_result))
-            else:
-                tmp_info_extract = None
-
-            if len(tmp_info_extract) > len(info_extract):
-                info_extract = tmp_info_extract
-                ocr_text = tmp_ocr_text
+        if len(tmp_info_extract) > len(info_extract):
+            info_extract = tmp_info_extract
+            ocr_text = tmp_ocr_text
+            rec_type = tmp_rec_type
 
     if info_extract:
         result_json = json.dumps(info_extract, ensure_ascii=False)
@@ -425,6 +416,29 @@ def cost_task(pk_phhd, cost_list_ie_result):
     return cost_data
 
 
+def parse_pdf_text(settlement_text):
+    pattern = (r'(?:交款人：(.*?)\n|住院时间：(.*?)至(.*?)\n|\(小写\)(.*?)\n|个人现金支付：(.*?)\n|个人账户支付：(.*?)\n'
+               r'|个人自费：(.*?)\n|医保类型：(.*?)\n|住院科别：(.*?)\n|住院号：(.*?)\n|票据号码：(.*?)\n|)')
+    # 查找所有匹配项
+    matches = re.findall(pattern, settlement_text)
+    results = {}
+    keys = ['患者姓名', '入院日期', '出院日期', '费用总额', '个人现金支付', '个人账户支付', '个人自费', '医保类型',
+            '科室', '住院号', '医保结算单号码']
+
+    for match in matches:
+        for key, value in zip(keys, match):
+            if value:
+                results[key] = [[{'text': value, 'probability': 1}]]
+    settlement_key = ['患者姓名', '入院日期', '出院日期', '费用总额', '个人现金支付', '个人账户支付', '个人自费',
+                      '医保类型', '住院号', '医保结算单号码']
+    discharge_key = ['科室', '患者姓名', '入院日期', '出院日期', '住院号']
+    cost_key = ['患者姓名', '入院日期', '出院日期', '费用总额']
+    settlement_result = {key: results[key] for key in settlement_key if key in results}
+    discharge_result = {key: results[key] for key in discharge_key if key in results}
+    cost_result = {key: results[key] for key in cost_key if key in results}
+    return settlement_result, discharge_result, cost_result
+
+
 def photo_review(pk_phhd, name):
     """
     处理单个报销案子
@@ -438,7 +452,7 @@ def photo_review(pk_phhd, name):
     session = MysqlSession()
     phrecs = session.query(ZxPhrec.pk_phrec, ZxPhrec.cRectype, ZxPhrec.cfjaddress).filter(
         ZxPhrec.pk_phhd == pk_phhd
-    ).all()
+    ).order_by(ZxPhrec.cRectype).all()
     session.close()
 
     # 同一批图的标识
@@ -446,25 +460,76 @@ def photo_review(pk_phhd, name):
     processed_img_dir = common_util.get_processed_img_path('')
     os.makedirs(processed_img_dir, exist_ok=True)
 
-    discharge_text = ''
+    has_pdf = False  # 是否获取到了pdf，获取到可以直接利用pdf更快的获取信息
+    better_settlement_path = None
+    better_cost_path = None
+    settlement_text = ''
     for phrec in phrecs:
-        rec_type, ie_result, ocr_text = information_extraction(phrec, pk_phhd)
-        if rec_type == '基本医保结算单':
-            rec_result = settlement_result
-        elif rec_type == '出院记录':
-            rec_result = discharge_result
-            discharge_text += ocr_text
-        elif rec_type == '费用清单':
-            rec_result = cost_result
-        else:
-            rec_result = None
-        if rec_result is not None:
-            for key, value in ie_result.items():
-                rec_result[key].append(value)
+        original_img_path = common_util.get_img_path(phrec.cfjaddress)
+        if not original_img_path:
+            img_url = ufile.get_private_url(phrec.cfjaddress)
+            if not img_url:
+                continue
+            original_img_path = common_util.save_to_local(img_url)
+        img_path = common_util.get_processed_img_path(phrec.cfjaddress)
+        shutil.copy2(original_img_path, img_path)
+        # 尝试从二维码中获取高清图片
+        better_settlement_path, settlement_text, better_cost_path = parse_qrcode(img_path, phrec.cfjaddress)
+        if better_settlement_path:
+            has_pdf = True
+            break
 
-    # 删除多余图片
-    if os.path.exists(processed_img_dir) and os.path.isdir(processed_img_dir):
-        shutil.rmtree(processed_img_dir)
+    discharge_text = ''
+    if has_pdf:
+        settlement_result, discharge_result, cost_result = parse_pdf_text(settlement_text)
+        discharge_result = defaultdict(list, discharge_result)
+
+        is_settlement_updated = False
+        is_cost_updated = False
+        for phrec in phrecs:
+            if phrec.cRectype == '1':
+                if not is_settlement_updated:
+                    try:
+                        ufile.copy_file(BUCKET, phrec.cfjaddress, "drg2015", phrec.cfjaddress)
+                        ufile.upload_file(phrec.cfjaddress, better_settlement_path)
+                    except Exception as e:
+                        logging.error("更新结算单pdf图片出错", exc_info=e)
+                    finally:
+                        is_settlement_updated = True
+            elif phrec.cRectype == '3':
+                rec_type, ie_result, ocr_text = information_extraction(phrec, pk_phhd)
+                if rec_type == '出院记录':
+                    discharge_text += ocr_text
+                    for key, value in ie_result.items():
+                        discharge_result[key].append(value)
+            elif phrec.cRectype == '4':
+                if not is_cost_updated:
+                    try:
+                        ufile.copy_file(BUCKET, phrec.cfjaddress, "drg2015", phrec.cfjaddress)
+                        ufile.upload_file(phrec.cfjaddress, better_cost_path)
+                    except Exception as e:
+                        logging.error("更新费用清单pdf图片出错", exc_info=e)
+                    finally:
+                        is_cost_updated = True
+    else:
+        for phrec in phrecs:
+            rec_type, ie_result, ocr_text = information_extraction(phrec, pk_phhd)
+            if rec_type == '基本医保结算单':
+                rec_result = settlement_result
+            elif rec_type == '出院记录':
+                rec_result = discharge_result
+                discharge_text += ocr_text
+            elif rec_type == '费用清单':
+                rec_result = cost_result
+            else:
+                rec_result = None
+            if rec_result is not None:
+                for key, value in ie_result.items():
+                    rec_result[key].append(value)
+
+        # 删除多余图片
+        if os.path.exists(processed_img_dir) and os.path.isdir(processed_img_dir):
+            shutil.rmtree(processed_img_dir)
 
     settlement_data = settlement_task(pk_phhd, settlement_result)
     discharge_data = discharge_task(pk_phhd, discharge_result)
@@ -560,8 +625,9 @@ def photo_review(pk_phhd, name):
         else:
             review_result['discharge_date_match'] = '0'
 
-    review_result['consistency'] = (review_result['name_match'] == '1' and review_result['admission_date_match'] == '1'
-                                    and review_result['discharge_date_match'] == '1')
+    review_result['consistency'] = (
+            review_result['name_match'] == '1' and review_result['admission_date_match'] == '1'
+            and review_result['discharge_date_match'] == '1')
 
     review_result['success'] = review_result['integrity'] and review_result['consistency']
     save_or_update_ie(ZxIeReview, pk_phhd, review_result)
diff --git a/util/image_util.py b/util/image_util.py
index 3eee353..4388dc1 100644
--- a/util/image_util.py
+++ b/util/image_util.py
@@ -1,6 +1,8 @@
+import logging
 import math
 
 import cv2
+import fitz
 import numpy
 from PIL import Image
 
@@ -27,7 +29,7 @@ def capture(image, rectangle):
 def split(img_path, ratio=1.414, overlap=0.05, x_compensation=3):
     """
     分割图片
-    :param img_path:图片路径
+    :param img_path: 图片路径
     :param ratio: 分割后的比例
     :param overlap: 图片之间的覆盖比例
     :param x_compensation: 横向补偿倍率
@@ -251,3 +253,33 @@ def is_photo(img_path):
         if any(tag in exif for tag in (271, 272)):
             return True
     return False
+
+
+def pdf_to_imgs(pdf_path, dpi=150):
+    pdf_file = None
+    # 定义缩放系数（DPI）
+    default_dpi = 72
+    zoom = dpi / default_dpi
+    try:
+        # 打开PDF文件
+        pdf_file = fitz.open(pdf_path)
+
+        pdf_imgs = []
+        for page in pdf_file:
+            # 设置矩阵变换参数
+            mat = fitz.Matrix(zoom, zoom)
+            # 渲染页面
+            pix = page.get_pixmap(matrix=mat)
+            # 将渲染结果转换为OpenCV兼容的格式
+            img = numpy.frombuffer(pix.samples, dtype=numpy.uint8).reshape((pix.height, pix.width, -1))
+            img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
+            pdf_imgs.append([img, page.get_text()])
+
+        return pdf_imgs
+
+    except Exception as ex:
+        logging.getLogger('error').error('pdf转图片失败！', exc_info=ex)
+        return None
+    finally:
+        if pdf_file:
+            pdf_file.close()