# Deep Learning-Based Flap Detection System Using Thermographic Images in Plastic Surgery
## 4 Discussion
This necessitates close postoperative monitoring by skilled plastic surgeons at regular intervals to detect and address complications promptly. Traditionally, clinical examination of the flap, assessing factors like skin color, temperature, and capillary refill time, along with Acoustic Doppler Sonography (ADS) to evaluate microsurgical anastomoses, has been the gold standard, though these methods are subjective and require expert interpretation [50; 51]. Studies have shown that thermal cameras can detect flap compromise as early as 2 h postoperatively, significantly earlier than clinical examination, by identifying temperature differences between compromised and viable flaps [52; 53]. These differences, ranging from 2.4 \({}^{\circ}\)C to 5.4 \({}^{\circ}\)C in compromised flaps, provide objective data that can enhance early diagnosis and intervention, thereby improving patient outcomes [32]. There are variations in the temperature difference between a flap and the surrounding skin, depending on the type of flap. These variations arise primarily from differences in blood supply, tissue composition, and the method of flap creation [54]. The perfusion of random pattern-based flaps is more unpredictable due to the dependence on the random vascularization of nearby vessels. In general, the distal portion of these flaps tends to have less reliable perfusion, which is to be expected [55]. By contrast, axial or pedicled flaps are characterized by a well-defined blood supply provided by a single artery or vein that runs along the flap. These flaps often possess a higher degree of thermal stability and a smaller temperature difference in comparison to the surrounding skin [56]. The surgical manipulation of the tissue may nevertheless cause a slight decrease in temperature. The free flaps are entirely detached from their original blood supply and subsequently reattached via microsurgical techniques. It is not uncommon for these flaps to have a slightly lower temperature than the surrounding skin at the initial stage following the procedure, due to the disruption of blood flow [52]. With the normalization of blood flow over time, the temperature discrepancy should diminish [57]. To fulfill our intended purpose, we chose the thermographic camera based on the considerations mentioned previously, benefiting from its affordability, portability, and non-invasiveness. This method of imaging is also intuitive, allowing for easy interpretation and replication, with a minimal learning curve. However, this technique's limitations are related to the inconsistency of the measured data, the subjectivity and experience of the person who interprets the results, and the influence of external environmental factors (temperature, humidity, and light) on the temperatures indicated by the device [58]. To overcome these limitations, we proposed and strictly adhered to the image acquisition protocol described above, but these limitations must be taken into consideration when interpreting the thermographic images and the results obtained by the proposed algorithm. It is advisable to consider the temperature differences between the areas of interest and adjacent areas, rather than the absolute temperature values to minimize the influence of other factors [32]. The image obtained by these devices captures the infrared radiation emitted by the skin, thus accurately attributing to each pixel a precise temperature. This provides a cartography of the temperatures at this level and is subsequently a marker of the flap's blood flow [59]. The algorithm developed by our multidisciplinary team offers a distinct advantage in that, once the image has been segmented, it is capable of extracting the temperature of each pixel. It is therefore possible to calculate the average temperature of the surgical area, particularly the flap, and to compare it with the temperatures of the surrounding tissue.